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StarPilot
This commit is contained in:
firestar5683
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char id=10005 x=899 y=854 width=73 height=73 xoffset=9 yoffset=67 xadvance=90 page=0 chnl=15
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 195 KiB |
@@ -10,7 +10,7 @@ TRANSLATIONS_DIR = SELFDRIVE_DIR / "ui" / "translations"
|
||||
LANGUAGES_FILE = TRANSLATIONS_DIR / "languages.json"
|
||||
|
||||
GLYPH_PADDING = 6
|
||||
EXTRA_CHARS = "–‑✓×°§•X⚙✕◀▶✔⌫⇧␣○●↳çêüñ–‑✓×°§•€£¥"
|
||||
EXTRA_CHARS = "–‑✓×°§•X⚙✕◀▶✔⌫⇧␣○●↳çêüñ–‑✓×°§•€£¥²"
|
||||
UNIFONT_LANGUAGES = {"ar", "th", "zh-CHT", "zh-CHS", "ko", "ja"}
|
||||
|
||||
|
||||
@@ -48,16 +48,18 @@ def _glyph_metrics(glyphs, rects, codepoints):
|
||||
offset_y = int(round(glyph.offsetY))
|
||||
min_offset_y = offset_y if min_offset_y is None else min(min_offset_y, offset_y)
|
||||
max_extent = max(max_extent, offset_y + height)
|
||||
entries.append({
|
||||
"id": codepoint,
|
||||
"x": int(round(rect.x)),
|
||||
"y": int(round(rect.y)),
|
||||
"width": width,
|
||||
"height": height,
|
||||
"xoffset": int(round(glyph.offsetX)),
|
||||
"yoffset": offset_y,
|
||||
"xadvance": int(round(glyph.advanceX)),
|
||||
})
|
||||
entries.append(
|
||||
{
|
||||
"id": codepoint,
|
||||
"x": int(round(rect.x)),
|
||||
"y": int(round(rect.y)),
|
||||
"width": width,
|
||||
"height": height,
|
||||
"xoffset": int(round(glyph.offsetX)),
|
||||
"yoffset": offset_y,
|
||||
"xadvance": int(round(glyph.advanceX)),
|
||||
}
|
||||
)
|
||||
|
||||
if min_offset_y is None:
|
||||
raise RuntimeError("No glyphs were generated")
|
||||
@@ -80,8 +82,10 @@ def _write_bmfont(path: Path, font_size: int, face: str, atlas_name: str, line_h
|
||||
]
|
||||
for entry in entries:
|
||||
lines.append(
|
||||
("char id={id:<4} x={x:<5} y={y:<5} width={width:<5} height={height:<5} " +
|
||||
"xoffset={xoffset:<5} yoffset={yoffset:<5} xadvance={xadvance:<5} page=0 chnl=15").format(**entry)
|
||||
(
|
||||
"char id={id:<4} x={x:<5} y={y:<5} width={width:<5} height={height:<5} "
|
||||
+ "xoffset={xoffset:<5} yoffset={yoffset:<5} xadvance={xadvance:<5} page=0 chnl=15"
|
||||
).format(**entry)
|
||||
)
|
||||
path.write_text("\n".join(lines) + "\n")
|
||||
|
||||
|
||||
@@ -0,0 +1,157 @@
|
||||
info face="unifont" size=-16 bold=0 italic=0 charset="" unicode=1 stretchH=100 smooth=0 aa=1 padding=0,0,0,0 spacing=0,0 outline=0
|
||||
common lineHeight=16 base=16 scaleW=512 scaleH=256 pages=1 packed=0 alphaChnl=0 redChnl=4 greenChnl=4 blueChnl=4
|
||||
page id=0 file="unifont.png"
|
||||
chars count=153
|
||||
char id=32 x=6 y=6 width=8 height=16 xoffset=0 yoffset=0 xadvance=8 page=0 chnl=15
|
||||
char id=33 x=26 y=6 width=1 height=10 xoffset=4 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=34 x=39 y=6 width=5 height=4 xoffset=2 yoffset=2 xadvance=8 page=0 chnl=15
|
||||
char id=35 x=56 y=6 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=36 x=74 y=6 width=7 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=37 x=93 y=6 width=7 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=38 x=112 y=6 width=7 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=39 x=131 y=6 width=1 height=4 xoffset=4 yoffset=2 xadvance=8 page=0 chnl=15
|
||||
char id=40 x=144 y=6 width=3 height=12 xoffset=3 yoffset=3 xadvance=8 page=0 chnl=15
|
||||
char id=41 x=159 y=6 width=3 height=12 xoffset=2 yoffset=3 xadvance=8 page=0 chnl=15
|
||||
char id=42 x=174 y=6 width=7 height=7 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=43 x=193 y=6 width=7 height=7 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=44 x=212 y=6 width=2 height=4 xoffset=3 yoffset=12 xadvance=8 page=0 chnl=15
|
||||
char id=45 x=226 y=6 width=4 height=1 xoffset=2 yoffset=9 xadvance=8 page=0 chnl=15
|
||||
char id=46 x=242 y=6 width=2 height=2 xoffset=3 yoffset=12 xadvance=8 page=0 chnl=15
|
||||
char id=47 x=256 y=6 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=48 x=274 y=6 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=49 x=292 y=6 width=5 height=10 xoffset=2 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=50 x=309 y=6 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=51 x=327 y=6 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=52 x=345 y=6 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=53 x=363 y=6 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=54 x=381 y=6 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=55 x=399 y=6 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=56 x=417 y=6 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=57 x=435 y=6 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=58 x=453 y=6 width=2 height=7 xoffset=3 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=59 x=467 y=6 width=2 height=9 xoffset=3 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=60 x=481 y=6 width=5 height=9 xoffset=2 yoffset=5 xadvance=8 page=0 chnl=15
|
||||
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|
||||
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|
||||
char id=63 x=41 y=34 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
char id=69 x=149 y=34 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
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|
||||
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|
||||
char id=72 x=203 y=34 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=73 x=221 y=34 width=5 height=10 xoffset=2 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=74 x=238 y=34 width=7 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=75 x=257 y=34 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
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|
||||
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|
||||
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|
||||
char id=79 x=329 y=34 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=80 x=347 y=34 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
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|
||||
char id=82 x=384 y=34 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=83 x=402 y=34 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=84 x=420 y=34 width=7 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=85 x=439 y=34 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=86 x=457 y=34 width=7 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=87 x=476 y=34 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=88 x=6 y=62 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
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|
||||
char id=90 x=43 y=62 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=91 x=61 y=62 width=3 height=12 xoffset=4 yoffset=3 xadvance=8 page=0 chnl=15
|
||||
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|
||||
char id=93 x=94 y=62 width=3 height=12 xoffset=1 yoffset=3 xadvance=8 page=0 chnl=15
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
char id=102 x=251 y=62 width=5 height=11 xoffset=1 yoffset=3 xadvance=8 page=0 chnl=15
|
||||
char id=103 x=268 y=62 width=6 height=11 xoffset=1 yoffset=5 xadvance=8 page=0 chnl=15
|
||||
char id=104 x=286 y=62 width=6 height=11 xoffset=1 yoffset=3 xadvance=8 page=0 chnl=15
|
||||
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|
||||
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|
||||
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|
||||
char id=108 x=356 y=62 width=5 height=11 xoffset=2 yoffset=3 xadvance=8 page=0 chnl=15
|
||||
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|
||||
char id=110 x=392 y=62 width=6 height=8 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=111 x=410 y=62 width=6 height=8 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=112 x=428 y=62 width=6 height=10 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
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|
||||
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|
||||
char id=115 x=482 y=62 width=6 height=8 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=116 x=6 y=90 width=5 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
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|
||||
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|
||||
char id=119 x=59 y=90 width=7 height=8 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=120 x=78 y=90 width=6 height=8 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=121 x=96 y=90 width=6 height=10 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=122 x=114 y=90 width=6 height=8 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=123 x=132 y=90 width=4 height=13 xoffset=2 yoffset=3 xadvance=8 page=0 chnl=15
|
||||
char id=124 x=148 y=90 width=1 height=14 xoffset=4 yoffset=2 xadvance=8 page=0 chnl=15
|
||||
char id=125 x=161 y=90 width=4 height=13 xoffset=2 yoffset=3 xadvance=8 page=0 chnl=15
|
||||
char id=126 x=177 y=90 width=7 height=3 xoffset=1 yoffset=3 xadvance=8 page=0 chnl=15
|
||||
char id=163 x=196 y=90 width=7 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=165 x=215 y=90 width=7 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=167 x=234 y=90 width=6 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=176 x=252 y=90 width=4 height=4 xoffset=2 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
char id=178 x=268 y=90 width=5 height=7 xoffset=1 yoffset=3 xadvance=8 page=0 chnl=15
|
||||
char id=215 x=285 y=90 width=6 height=5 xoffset=1 yoffset=7 xadvance=8 page=0 chnl=15
|
||||
char id=231 x=303 y=90 width=6 height=10 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=234 x=321 y=90 width=6 height=12 xoffset=1 yoffset=2 xadvance=8 page=0 chnl=15
|
||||
char id=241 x=339 y=90 width=6 height=12 xoffset=1 yoffset=2 xadvance=8 page=0 chnl=15
|
||||
char id=252 x=357 y=90 width=6 height=12 xoffset=1 yoffset=2 xadvance=8 page=0 chnl=15
|
||||
char id=1059 x=375 y=90 width=7 height=10 xoffset=1 yoffset=4 xadvance=8 page=0 chnl=15
|
||||
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|
||||
char id=1082 x=412 y=90 width=6 height=8 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=1085 x=430 y=90 width=6 height=8 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
char id=1593 x=88 y=118 width=6 height=9 xoffset=1 yoffset=7 xadvance=8 page=0 chnl=15
|
||||
char id=1604 x=106 y=118 width=6 height=11 xoffset=1 yoffset=3 xadvance=8 page=0 chnl=15
|
||||
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|
||||
char id=3607 x=142 y=118 width=6 height=8 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=3618 x=160 y=118 width=6 height=8 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=3652 x=178 y=118 width=6 height=11 xoffset=1 yoffset=3 xadvance=8 page=0 chnl=15
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
char id=8627 x=265 y=118 width=5 height=12 xoffset=2 yoffset=0 xadvance=8 page=0 chnl=15
|
||||
char id=8679 x=282 y=118 width=7 height=12 xoffset=1 yoffset=2 xadvance=8 page=0 chnl=15
|
||||
char id=9003 x=301 y=118 width=8 height=5 xoffset=0 yoffset=7 xadvance=8 page=0 chnl=15
|
||||
char id=9251 x=321 y=118 width=6 height=2 xoffset=1 yoffset=12 xadvance=8 page=0 chnl=15
|
||||
char id=9654 x=339 y=118 width=6 height=6 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=9664 x=357 y=118 width=6 height=6 xoffset=1 yoffset=6 xadvance=8 page=0 chnl=15
|
||||
char id=9675 x=375 y=118 width=7 height=7 xoffset=1 yoffset=5 xadvance=8 page=0 chnl=15
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
char id=26412 x=104 y=146 width=15 height=16 xoffset=0 yoffset=0 xadvance=16 page=0 chnl=15
|
||||
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|
||||
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|
||||
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|
||||
char id=39636 x=212 y=146 width=15 height=16 xoffset=0 yoffset=0 xadvance=16 page=0 chnl=15
|
||||
char id=44397 x=239 y=146 width=15 height=14 xoffset=1 yoffset=2 xadvance=16 page=0 chnl=15
|
||||
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||||
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|
||||
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@@ -46,6 +46,7 @@ class CarSpecificEvents:
|
||||
|
||||
self.steering_unpressed = 0
|
||||
self.low_speed_alert = False
|
||||
self.gm_low_speed_alert_shown = False
|
||||
self.no_steer_warning = False
|
||||
self.silent_steer_warning = True
|
||||
|
||||
@@ -111,7 +112,17 @@ class CarSpecificEvents:
|
||||
events.add(EventName.manualRestart)
|
||||
|
||||
elif self.CP.brand == 'gm':
|
||||
events = self.create_common_events(CS, CS_prev, extra_gears=extra_gears, pcm_enable=self.CP.pcmCruise)
|
||||
events = self.create_common_events(CS, CS_prev, extra_gears=extra_gears, pcm_enable=self.CP.pcmCruise,
|
||||
suppress_low_speed_alert=True)
|
||||
|
||||
# StarPilot behavior: show the low-speed steer alert once per ignition cycle.
|
||||
if (not CS.cruiseState.available and not CS_prev.cruiseState.available and
|
||||
CS.vEgo < 0.1 and not CC.enabled):
|
||||
self.gm_low_speed_alert_shown = False
|
||||
|
||||
if CS.lowSpeedAlert and not self.gm_low_speed_alert_shown:
|
||||
events.add(EventName.belowSteerSpeed)
|
||||
self.gm_low_speed_alert_shown = True
|
||||
|
||||
# Enabling at a standstill with brake is allowed
|
||||
# TODO: verify 17 Volt can enable for the first time at a stop and allow for all GMs
|
||||
@@ -147,7 +158,7 @@ class CarSpecificEvents:
|
||||
return events
|
||||
|
||||
def create_common_events(self, CS: structs.CarState, CS_prev: car.CarState, extra_gears: list | None = None, pcm_enable=True,
|
||||
allow_button_cancel=True):
|
||||
allow_button_cancel=True, suppress_low_speed_alert=False):
|
||||
events = Events()
|
||||
|
||||
if CS.doorOpen:
|
||||
@@ -191,7 +202,7 @@ class CarSpecificEvents:
|
||||
events.add(EventName.vehicleSensorsInvalid)
|
||||
if CS.invalidLkasSetting:
|
||||
events.add(EventName.invalidLkasSetting)
|
||||
if CS.lowSpeedAlert:
|
||||
if CS.lowSpeedAlert and not suppress_low_speed_alert:
|
||||
events.add(EventName.belowSteerSpeed)
|
||||
if CS.buttonEnable:
|
||||
events.add(EventName.buttonEnable)
|
||||
|
||||
@@ -177,6 +177,8 @@ class Car:
|
||||
|
||||
if self.frogpilot_toggles.always_on_lateral:
|
||||
self.FPCP.alternativeExperience |= ALTERNATIVE_EXPERIENCE.ALWAYS_ON_LATERAL
|
||||
if getattr(self.frogpilot_toggles, "remap_cancel_to_distance", False):
|
||||
self.FPCP.alternativeExperience |= ALTERNATIVE_EXPERIENCE.GM_REMAP_CANCEL_TO_DISTANCE
|
||||
|
||||
fpcp_bytes = self.FPCP.to_bytes()
|
||||
self.params.put("FrogPilotCarParams", fpcp_bytes)
|
||||
|
||||
@@ -141,12 +141,12 @@ class VCruiseHelper:
|
||||
if self.CP.pcmCruise and not self.gm_cc_only:
|
||||
return
|
||||
|
||||
initial = V_CRUISE_INITIAL_EXPERIMENTAL_MODE if experimental_mode and not frogpilot_toggles.conditional_experimental_mode else V_CRUISE_INITIAL
|
||||
engage_floor_kph = max(V_CRUISE_MIN, 7.0 * CV.MPH_TO_KPH)
|
||||
|
||||
if (any(b.type in (ButtonType.accelCruise, ButtonType.resumeCruise) for b in CS.buttonEvents)
|
||||
and self.v_cruise_initialized or (self.gm_cc_only and resume_prev_button)):
|
||||
self.v_cruise_kph = self.v_cruise_kph_last
|
||||
else:
|
||||
self.v_cruise_kph = int(round(np.clip(CS.vEgo * CV.MS_TO_KPH, initial, V_CRUISE_MAX)))
|
||||
self.v_cruise_kph = int(round(np.clip(CS.vEgo * CV.MS_TO_KPH, engage_floor_kph, V_CRUISE_MAX)))
|
||||
|
||||
self.v_cruise_cluster_kph = self.v_cruise_kph
|
||||
|
||||
@@ -133,6 +133,7 @@ class Controls:
|
||||
|
||||
# accel PID loop
|
||||
pid_accel_limits = self.CI.get_pid_accel_limits(self.CP, CS.vEgo, CS.vCruise * CV.KPH_TO_MS)
|
||||
self.LoC.experimental_mode = bool(self.sm['selfdriveState'].experimentalMode)
|
||||
actuators.accel = float(min(self.LoC.update(CC.longActive, CS, long_plan.aTarget, long_plan.shouldStop, pid_accel_limits, self.frogpilot_toggles), self.frogpilot_toggles.max_desired_acceleration))
|
||||
|
||||
# Steering PID loop and lateral MPC
|
||||
|
||||
@@ -54,6 +54,10 @@ def get_accel_from_plan(speeds, accels, t_idxs, action_t=DT_MDL, vEgoStopping=0.
|
||||
v_target_1sec < vEgoStopping)
|
||||
return a_target, should_stop
|
||||
|
||||
|
||||
# Backward-compatible alias used by StarPilot tinygrad_modeld.
|
||||
get_accel_from_plan_tomb_raider = get_accel_from_plan
|
||||
|
||||
def curv_from_psis(psi_target, psi_rate, vego, action_t):
|
||||
vego = np.clip(vego, MIN_SPEED, np.inf)
|
||||
curv_from_psi = psi_target / (vego * action_t)
|
||||
|
||||
@@ -3,11 +3,13 @@ import numpy as np
|
||||
from collections import deque
|
||||
|
||||
from cereal import log
|
||||
from opendbc.car.lateral import FRICTION_THRESHOLD, get_friction
|
||||
from openpilot.common.constants import ACCELERATION_DUE_TO_GRAVITY
|
||||
from opendbc.car.gm.values import CAR as GM_CAR
|
||||
from opendbc.car.lateral import get_friction
|
||||
from openpilot.common.constants import ACCELERATION_DUE_TO_GRAVITY, CV
|
||||
from openpilot.common.filter_simple import FirstOrderFilter
|
||||
from openpilot.selfdrive.controls.lib.latcontrol import LatControl
|
||||
from openpilot.common.pid import PIDController
|
||||
from openpilot.selfdrive.controls.lib.drive_helpers import MIN_SPEED
|
||||
from openpilot.selfdrive.controls.lib.latcontrol import LatControl
|
||||
|
||||
# At higher speeds (25+mph) we can assume:
|
||||
# Lateral acceleration achieved by a specific car correlates to
|
||||
@@ -20,15 +22,46 @@ from openpilot.common.pid import PIDController
|
||||
# Additionally, there is friction in the steering wheel that needs
|
||||
# to be overcome to move it at all, this is compensated for too.
|
||||
|
||||
KP = 1.0
|
||||
KI = 0.3
|
||||
KD = 0.0
|
||||
KP = 0.7
|
||||
KI = 0.35
|
||||
|
||||
INTERP_SPEEDS = [1, 1.5, 2.0, 3.0, 5, 7.5, 10, 15, 30]
|
||||
KP_INTERP = [250, 120, 65, 30, 11.5, 5.5, 3.5, 2.0, KP]
|
||||
|
||||
LOW_SPEED_X = [0, 10, 20, 30]
|
||||
LOW_SPEED_Y = [12, 10.5, 8, 5]
|
||||
MAX_LAT_JERK_UP = 2.5 # m/s^3
|
||||
|
||||
LP_FILTER_CUTOFF_HZ = 1.2
|
||||
JERK_LOOKAHEAD_SECONDS = 0.19
|
||||
JERK_GAIN = 0.22
|
||||
LAT_ACCEL_REQUEST_BUFFER_SECONDS = 1.0
|
||||
VERSION = 0
|
||||
VERSION = 2
|
||||
DEBUG_TORQUE_TUNE = False
|
||||
FF_SCALE_BLEND_LAT_ACCEL = 0.05
|
||||
DEADZONE_BOOST_LAT_ACCEL = 0.15
|
||||
UNWIND_D_DES_THRESHOLD = -1.0
|
||||
UNWIND_LAT_ACCEL_NEAR_ZERO = 0.3
|
||||
MIN_LATERAL_CONTROL_SPEED = 0.3
|
||||
|
||||
BOLT_2022_2023_CARS = (
|
||||
GM_CAR.CHEVROLET_BOLT_ACC_2022_2023,
|
||||
GM_CAR.CHEVROLET_BOLT_ACC_2022_2023_PEDAL,
|
||||
GM_CAR.CHEVROLET_BOLT_CC_2022_2023,
|
||||
)
|
||||
BOLT_2018_2021_CARS = (
|
||||
GM_CAR.CHEVROLET_BOLT_CC_2018_2021,
|
||||
)
|
||||
BOLT_2017_CARS = (
|
||||
GM_CAR.CHEVROLET_BOLT_CC_2017,
|
||||
)
|
||||
BOLT_CARS = BOLT_2022_2023_CARS + BOLT_2018_2021_CARS + BOLT_2017_CARS
|
||||
|
||||
|
||||
def get_friction_threshold(v_ego: float) -> float:
|
||||
# Keep StarPilot's speed-scaled friction threshold behavior.
|
||||
return float(np.interp(v_ego, [1 * CV.MPH_TO_MS, 20 * CV.MPH_TO_MS, 75 * CV.MPH_TO_MS], [0.16, 0.19, 0.27]))
|
||||
|
||||
|
||||
class LatControlTorque(LatControl):
|
||||
def __init__(self, CP, CI, dt):
|
||||
@@ -36,13 +69,41 @@ class LatControlTorque(LatControl):
|
||||
self.torque_params = CP.lateralTuning.torque.as_builder()
|
||||
self.torque_from_lateral_accel = CI.torque_from_lateral_accel()
|
||||
self.lateral_accel_from_torque = CI.lateral_accel_from_torque()
|
||||
self.pid = PIDController([INTERP_SPEEDS, KP_INTERP], KI, KD, rate=1/self.dt)
|
||||
self.pid = PIDController([INTERP_SPEEDS, KP_INTERP], KI, rate=1/self.dt)
|
||||
self.update_limits()
|
||||
self.steering_angle_deadzone_deg = self.torque_params.steeringAngleDeadzoneDeg
|
||||
self.lat_accel_request_buffer_len = int(LAT_ACCEL_REQUEST_BUFFER_SECONDS / self.dt)
|
||||
self.lat_accel_request_buffer = deque([0.] * self.lat_accel_request_buffer_len , maxlen=self.lat_accel_request_buffer_len)
|
||||
self.lat_accel_request_buffer = deque([0.] * self.lat_accel_request_buffer_len, maxlen=self.lat_accel_request_buffer_len)
|
||||
self.lookahead_frames = int(JERK_LOOKAHEAD_SECONDS / self.dt)
|
||||
self.jerk_filter = FirstOrderFilter(0.0, 1 / (2 * np.pi * LP_FILTER_CUTOFF_HZ), self.dt)
|
||||
self.previous_measurement = 0.0
|
||||
self.measurement_rate_filter = FirstOrderFilter(0.0, 1 / (2 * np.pi * LP_FILTER_CUTOFF_HZ), self.dt)
|
||||
self.measurement_rate_filter = FirstOrderFilter(0.0, 1 / (2 * np.pi * (MAX_LAT_JERK_UP - 0.5)), self.dt)
|
||||
self.low_speed_reset_threshold = max(CP.minSteerSpeed, MIN_LATERAL_CONTROL_SPEED)
|
||||
self.steer_release_i_decay = 0.8
|
||||
self.prev_steering_pressed = False
|
||||
self.debug_counter = 0
|
||||
self.prev_desired_lateral_accel = 0.0
|
||||
|
||||
self.is_bolt = CP.carFingerprint in BOLT_CARS
|
||||
self.is_bolt_2022_2023 = CP.carFingerprint in BOLT_2022_2023_CARS
|
||||
self.is_bolt_2018_2021 = CP.carFingerprint in BOLT_2018_2021_CARS
|
||||
self.is_bolt_2017 = CP.carFingerprint in BOLT_2017_CARS
|
||||
self.use_bolt_ff_scaling = self.is_bolt_2022_2023 or self.is_bolt_2018_2021 or self.is_bolt_2017
|
||||
self.use_bolt_ki_multiplier = self.use_bolt_ff_scaling
|
||||
self.torque_ff_scale_pos = 1.0
|
||||
self.torque_ff_scale_neg = 1.0
|
||||
self.torque_deadzone_boost = float(getattr(self.torque_params, "kfDEPRECATED", 0.0))
|
||||
self.torque_ki_mult = 1.0
|
||||
|
||||
if self.is_bolt:
|
||||
kp_scale = getattr(self.torque_params, "kp", getattr(self.torque_params, "kpDEPRECATED", 1.0))
|
||||
ki_scale = getattr(self.torque_params, "ki", getattr(self.torque_params, "kiDEPRECATED", 1.0))
|
||||
kd_scale = getattr(self.torque_params, "kd", getattr(self.torque_params, "kdDEPRECATED", 1.0))
|
||||
self.torque_ff_scale_pos = float(kp_scale)
|
||||
self.torque_ff_scale_neg = float(ki_scale)
|
||||
self.torque_ki_mult = float(kd_scale)
|
||||
if self.use_bolt_ki_multiplier and self.torque_ki_mult > 0.0 and self.torque_ki_mult != 1.0:
|
||||
self.pid._k_i = [self.pid._k_i[0], [k * self.torque_ki_mult for k in self.pid._k_i[1]]]
|
||||
|
||||
def update_live_torque_params(self, latAccelFactor, latAccelOffset, friction):
|
||||
self.torque_params.latAccelFactor = latAccelFactor
|
||||
@@ -60,7 +121,15 @@ class LatControlTorque(LatControl):
|
||||
if not active:
|
||||
output_torque = 0.0
|
||||
pid_log.active = False
|
||||
self.pid.reset()
|
||||
self.previous_measurement = 0.0
|
||||
self.measurement_rate_filter.x = 0.0
|
||||
self.lat_accel_request_buffer = deque([0.] * self.lat_accel_request_buffer_len, maxlen=self.lat_accel_request_buffer_len)
|
||||
self.prev_desired_lateral_accel = 0.0
|
||||
else:
|
||||
if self.prev_steering_pressed and not CS.steeringPressed:
|
||||
self.pid.i *= self.steer_release_i_decay
|
||||
|
||||
measured_curvature = -VM.calc_curvature(math.radians(CS.steeringAngleDeg - params.angleOffsetDeg), CS.vEgo, params.roll)
|
||||
roll_compensation = params.roll * ACCELERATION_DUE_TO_GRAVITY
|
||||
curvature_deadzone = abs(VM.calc_curvature(math.radians(self.steering_angle_deadzone_deg), CS.vEgo, 0.0))
|
||||
@@ -68,33 +137,50 @@ class LatControlTorque(LatControl):
|
||||
|
||||
delay_frames = int(np.clip(lat_delay / self.dt, 1, self.lat_accel_request_buffer_len))
|
||||
expected_lateral_accel = self.lat_accel_request_buffer[-delay_frames]
|
||||
# TODO factor out lateral jerk from error to later replace it with delay independent alternative
|
||||
future_desired_lateral_accel = desired_curvature * CS.vEgo ** 2
|
||||
self.lat_accel_request_buffer.append(future_desired_lateral_accel)
|
||||
raw_lateral_jerk = (future_desired_lateral_accel - expected_lateral_accel) / max(lat_delay, self.dt)
|
||||
raw_lateral_jerk = np.clip(raw_lateral_jerk, -MAX_LAT_JERK_UP, MAX_LAT_JERK_UP)
|
||||
desired_lateral_jerk = np.clip(self.jerk_filter.update(raw_lateral_jerk), -MAX_LAT_JERK_UP, MAX_LAT_JERK_UP)
|
||||
gravity_adjusted_future_lateral_accel = future_desired_lateral_accel - roll_compensation
|
||||
desired_lateral_jerk = (future_desired_lateral_accel - expected_lateral_accel) / lat_delay
|
||||
setpoint = expected_lateral_accel + desired_lateral_jerk * lat_delay
|
||||
desired_lateral_accel_rate = (setpoint - self.prev_desired_lateral_accel) / self.dt
|
||||
unwind_detected = (desired_lateral_accel_rate < UNWIND_D_DES_THRESHOLD and
|
||||
abs(setpoint) < UNWIND_LAT_ACCEL_NEAR_ZERO)
|
||||
self.prev_desired_lateral_accel = setpoint
|
||||
|
||||
measurement = measured_curvature * CS.vEgo ** 2
|
||||
measurement_rate = self.measurement_rate_filter.update((measurement - self.previous_measurement) / self.dt)
|
||||
measurement_rate = np.clip(measurement_rate, -MAX_LAT_JERK_UP, MAX_LAT_JERK_UP)
|
||||
self.previous_measurement = measurement
|
||||
|
||||
setpoint = lat_delay * desired_lateral_jerk + expected_lateral_accel
|
||||
low_speed_factor = (np.interp(CS.vEgo, LOW_SPEED_X, LOW_SPEED_Y) / max(CS.vEgo, MIN_SPEED)) ** 2
|
||||
current_kp = np.interp(CS.vEgo, self.pid._k_p[0], self.pid._k_p[1])
|
||||
error = setpoint - measurement
|
||||
error_with_lsf = error * (1 + low_speed_factor / max(current_kp, 1e-3))
|
||||
|
||||
# do error correction in lateral acceleration space, convert at end to handle non-linear torque responses correctly
|
||||
pid_log.error = float(error)
|
||||
pid_log.error = float(error_with_lsf)
|
||||
ff = gravity_adjusted_future_lateral_accel
|
||||
# latAccelOffset corrects roll compensation bias from device roll misalignment relative to car roll
|
||||
ff -= self.torque_params.latAccelOffset
|
||||
# TODO jerk is weighted by lat_delay for legacy reasons, but should be made independent of it
|
||||
ff += get_friction(error, lateral_accel_deadzone, FRICTION_THRESHOLD, self.torque_params)
|
||||
ff_scale = 1.0
|
||||
if self.use_bolt_ff_scaling:
|
||||
ff_scale = np.interp(ff, [-FF_SCALE_BLEND_LAT_ACCEL, 0.0, FF_SCALE_BLEND_LAT_ACCEL],
|
||||
[self.torque_ff_scale_neg, 1.0, self.torque_ff_scale_pos])
|
||||
ff *= ff_scale
|
||||
ff += get_friction(error_with_lsf + JERK_GAIN * desired_lateral_jerk, lateral_accel_deadzone, get_friction_threshold(CS.vEgo), self.torque_params)
|
||||
deadzone_boost_active = False
|
||||
if self.torque_deadzone_boost > 0.0 and abs(gravity_adjusted_future_lateral_accel) < DEADZONE_BOOST_LAT_ACCEL:
|
||||
boost_scale = np.interp(abs(gravity_adjusted_future_lateral_accel), [0.0, DEADZONE_BOOST_LAT_ACCEL], [1.0, 0.0])
|
||||
ff += np.sign(gravity_adjusted_future_lateral_accel) * self.torque_deadzone_boost * boost_scale
|
||||
deadzone_boost_active = True
|
||||
|
||||
freeze_integrator = steer_limited_by_safety or CS.steeringPressed or CS.vEgo < 5
|
||||
output_lataccel = self.pid.update(pid_log.error,
|
||||
-measurement_rate,
|
||||
feedforward=ff,
|
||||
speed=CS.vEgo,
|
||||
freeze_integrator=freeze_integrator)
|
||||
if CS.vEgo < self.low_speed_reset_threshold:
|
||||
self.pid.reset()
|
||||
freeze_integrator = (steer_limited_by_safety or CS.steeringPressed or
|
||||
CS.vEgo < self.low_speed_reset_threshold or unwind_detected)
|
||||
output_lataccel = self.pid.update(pid_log.error, error_rate=-measurement_rate, speed=CS.vEgo, feedforward=ff, freeze_integrator=freeze_integrator)
|
||||
output_torque = self.torque_from_lateral_accel(output_lataccel, self.torque_params)
|
||||
|
||||
pid_log.active = True
|
||||
@@ -102,11 +188,19 @@ class LatControlTorque(LatControl):
|
||||
pid_log.i = float(self.pid.i)
|
||||
pid_log.d = float(self.pid.d)
|
||||
pid_log.f = float(self.pid.f)
|
||||
pid_log.output = float(-output_torque) # TODO: log lat accel?
|
||||
pid_log.output = float(-output_torque) # TODO: log lat accel?
|
||||
pid_log.actualLateralAccel = float(measurement)
|
||||
pid_log.desiredLateralAccel = float(setpoint)
|
||||
pid_log.desiredLateralJerk = float(desired_lateral_jerk)
|
||||
pid_log.saturated = bool(self._check_saturation(self.steer_max - abs(output_torque) < 1e-3, CS, steer_limited_by_safety, curvature_limited))
|
||||
|
||||
if DEBUG_TORQUE_TUNE and self.is_bolt:
|
||||
self.debug_counter += 1
|
||||
if self.debug_counter % 50 == 0:
|
||||
print(f"bolt_torque ff_scale={ff_scale:.3f} pos={self.torque_ff_scale_pos:.3f} "
|
||||
f"neg={self.torque_ff_scale_neg:.3f} deadzone_boost_active={deadzone_boost_active}")
|
||||
|
||||
self.prev_steering_pressed = CS.steeringPressed
|
||||
|
||||
# TODO left is positive in this convention
|
||||
return -output_torque, 0.0, pid_log
|
||||
|
||||
@@ -1,2 +1,4 @@
|
||||
acados_ocp_lat.json
|
||||
c_generated_code/
|
||||
c_generated_code/**
|
||||
!c_generated_code/acados_ocp_solver_pyx.so
|
||||
!c_generated_code/libacados_ocp_solver_lat.so
|
||||
|
||||
BIN
Binary file not shown.
BIN
Binary file not shown.
@@ -1,9 +1,11 @@
|
||||
import numpy as np
|
||||
from cereal import car
|
||||
from openpilot.common.realtime import DT_CTRL
|
||||
from openpilot.common.filter_simple import FirstOrderFilter
|
||||
from openpilot.selfdrive.controls.lib.drive_helpers import CONTROL_N
|
||||
from openpilot.common.pid import PIDController
|
||||
from openpilot.selfdrive.modeld.constants import ModelConstants
|
||||
from opendbc.car.gm.values import CarControllerParams, GMFlags
|
||||
|
||||
CONTROL_N_T_IDX = ModelConstants.T_IDXS[:CONTROL_N]
|
||||
|
||||
@@ -12,6 +14,8 @@ LongCtrlState = car.CarControl.Actuators.LongControlState
|
||||
|
||||
def long_control_state_trans(CP, active, long_control_state, v_ego,
|
||||
should_stop, brake_pressed, cruise_standstill, frogpilot_toggles):
|
||||
# Ignore cruise standstill if car has a gas interceptor.
|
||||
cruise_standstill = cruise_standstill and not CP.enableGasInterceptorDEPRECATED
|
||||
stopping_condition = should_stop
|
||||
starting_condition = (not should_stop and
|
||||
not cruise_standstill and
|
||||
@@ -48,13 +52,73 @@ class LongControl:
|
||||
def __init__(self, CP):
|
||||
self.CP = CP
|
||||
self.long_control_state = LongCtrlState.off
|
||||
self.experimental_mode = False
|
||||
self.pid = PIDController((CP.longitudinalTuning.kpBP, CP.longitudinalTuning.kpV),
|
||||
(CP.longitudinalTuning.kiBP, CP.longitudinalTuning.kiV),
|
||||
rate=1 / DT_CTRL)
|
||||
# Preserve legacy behavior when no feedforward gain is provided (default of 0.0).
|
||||
kf = getattr(CP.longitudinalTuning, 'kfDEPRECATED', 0.0)
|
||||
self.feedforward_gain = kf if kf != 0.0 else 1.0
|
||||
self._mode_setup()
|
||||
self.last_output_accel = 0.0
|
||||
self.last_a_target = 0.0
|
||||
self.integrator_hold_frames = 0
|
||||
self.is_gm_pedal_long = bool(
|
||||
CP.brand == "gm" and CP.enableGasInterceptorDEPRECATED and (CP.flags & GMFlags.PEDAL_LONG.value)
|
||||
)
|
||||
|
||||
def update_mpc_mode(self, experimental_mode: bool):
|
||||
new_mode = 'blended' if experimental_mode else 'acc'
|
||||
if self.transitioning and self.prev_mode == 'blended' and self.current_mode == 'acc':
|
||||
self.mode_transition_timer = 0.0
|
||||
|
||||
if new_mode != self.current_mode:
|
||||
self.prev_mode = self.current_mode
|
||||
self.transitioning = True
|
||||
self.mode_transition_timer = 0.0
|
||||
self.mode_transition_filter.x = self.last_output_accel
|
||||
self.current_mode = new_mode
|
||||
|
||||
if self.transitioning:
|
||||
self.mode_transition_timer += DT_CTRL
|
||||
if self.mode_transition_timer >= self.mode_transition_duration:
|
||||
self.transitioning = False
|
||||
|
||||
def _mode_setup(self):
|
||||
self.prev_mode = 'acc'
|
||||
self.current_mode = 'acc'
|
||||
self.mode_transition_filter = FirstOrderFilter(0.0, 0.5, DT_CTRL)
|
||||
self.mode_transition_timer = 0.0
|
||||
self.mode_transition_duration = 1.0
|
||||
self.transitioning = False
|
||||
|
||||
def reset(self):
|
||||
self.pid.reset()
|
||||
self.last_a_target = 0.0
|
||||
self.integrator_hold_frames = 0
|
||||
|
||||
def _get_pedal_long_freeze(self, a_target, error, v_ego, accel_limits):
|
||||
if not self.is_gm_pedal_long:
|
||||
self.last_a_target = a_target
|
||||
self.integrator_hold_frames = 0
|
||||
return False
|
||||
|
||||
handoff_threshold = np.interp(v_ego, [0.0, 4.0, 12.0, 25.0], [0.35, 0.45, 0.55, 0.70])
|
||||
if abs(a_target - self.last_a_target) > handoff_threshold:
|
||||
hold_frames = int(round(np.interp(v_ego, [0.0, 4.0, 12.0, 25.0], [25.0, 20.0, 14.0, 10.0])))
|
||||
self.integrator_hold_frames = max(self.integrator_hold_frames, hold_frames)
|
||||
self.last_a_target = a_target
|
||||
|
||||
if self.integrator_hold_frames > 0:
|
||||
self.integrator_hold_frames -= 1
|
||||
|
||||
sat_buffer = 0.03
|
||||
at_neg_sat = self.last_output_accel <= (accel_limits[0] + sat_buffer)
|
||||
at_pos_sat = self.last_output_accel >= (accel_limits[1] - sat_buffer)
|
||||
sat_pushing_lower = at_neg_sat and error < -0.05
|
||||
sat_pushing_upper = at_pos_sat and error > 0.05
|
||||
|
||||
return self.integrator_hold_frames > 0 or sat_pushing_lower or sat_pushing_upper
|
||||
|
||||
def update(self, active, CS, a_target, should_stop, accel_limits, frogpilot_toggles):
|
||||
"""Update longitudinal control. This updates the state machine and runs a PID loop"""
|
||||
@@ -76,16 +140,30 @@ class LongControl:
|
||||
self.reset()
|
||||
|
||||
elif self.long_control_state == LongCtrlState.starting:
|
||||
if frogpilot_toggles.human_acceleration:
|
||||
output_accel = max(a_target, frogpilot_toggles.startAccel)
|
||||
else:
|
||||
output_accel = frogpilot_toggles.startAccel
|
||||
output_accel = (a_target if frogpilot_toggles.human_acceleration else frogpilot_toggles.startAccel)
|
||||
self.reset()
|
||||
|
||||
else: # LongCtrlState.pid
|
||||
error = a_target - CS.aEgo
|
||||
output_accel = self.pid.update(error, speed=CS.vEgo,
|
||||
feedforward=a_target)
|
||||
self.update_mpc_mode(self.experimental_mode)
|
||||
freeze_integrator = self._get_pedal_long_freeze(a_target, error, CS.vEgo, accel_limits)
|
||||
raw_output_accel = self.pid.update(error, speed=CS.vEgo,
|
||||
feedforward=a_target * self.feedforward_gain,
|
||||
freeze_integrator=freeze_integrator)
|
||||
|
||||
if self.transitioning and self.prev_mode == 'acc' and self.current_mode == 'blended':
|
||||
if raw_output_accel < 0 and raw_output_accel < self.last_output_accel:
|
||||
progress = min(1.0, self.mode_transition_timer / self.mode_transition_duration)
|
||||
# Soften transition at low urgency, but keep sharp for high decel.
|
||||
urgency_denom = max(1e-3, abs(CarControllerParams.ACCEL_MIN))
|
||||
urgency = abs(raw_output_accel / urgency_denom)
|
||||
urgency_smooth = min(1.0, urgency ** 0.4)
|
||||
blend_factor = 1.0 - (1.0 - progress) * (1.0 - urgency_smooth)
|
||||
output_accel = self.last_output_accel + (raw_output_accel - self.last_output_accel) * blend_factor
|
||||
else:
|
||||
output_accel = raw_output_accel
|
||||
else:
|
||||
output_accel = raw_output_accel
|
||||
|
||||
self.last_output_accel = np.clip(output_accel, accel_limits[0], accel_limits[1])
|
||||
return self.last_output_accel
|
||||
|
||||
@@ -1,2 +1,4 @@
|
||||
acados_ocp_long.json
|
||||
c_generated_code/
|
||||
c_generated_code/**
|
||||
!c_generated_code/acados_ocp_solver_pyx.so
|
||||
!c_generated_code/libacados_ocp_solver_long.so
|
||||
|
||||
BIN
Binary file not shown.
Executable
BIN
Binary file not shown.
@@ -3,12 +3,21 @@ import os
|
||||
import time
|
||||
import numpy as np
|
||||
from cereal import log
|
||||
from opendbc.car.interfaces import ACCEL_MIN, ACCEL_MAX
|
||||
try:
|
||||
from opendbc.car.interfaces import ACCEL_MIN, ACCEL_MAX
|
||||
except Exception:
|
||||
# Build-time fallback for generated-code steps before full python extension availability.
|
||||
ACCEL_MIN = -3.5
|
||||
ACCEL_MAX = 2.0
|
||||
from openpilot.common.constants import CV
|
||||
from openpilot.common.filter_simple import FirstOrderFilter
|
||||
from openpilot.common.realtime import DT_MDL
|
||||
from openpilot.common.swaglog import cloudlog
|
||||
# WARNING: imports outside of constants will not trigger a rebuild
|
||||
from openpilot.selfdrive.modeld.constants import index_function
|
||||
from openpilot.selfdrive.controls.radard import _LEAD_ACCEL_TAU
|
||||
|
||||
# Keep in sync with selfdrive/controls/radard.py
|
||||
_LEAD_ACCEL_TAU = 1.5
|
||||
|
||||
if __name__ == '__main__': # generating code
|
||||
from openpilot.third_party.acados.acados_template import AcadosModel, AcadosOcp, AcadosOcpSolver
|
||||
@@ -31,12 +40,25 @@ COST_E_DIM = 5
|
||||
COST_DIM = COST_E_DIM + 1
|
||||
CONSTR_DIM = 4
|
||||
|
||||
X_EGO_OBSTACLE_COST = 3.
|
||||
# ===== VOACC SPEED-BASED TUNING PARAMETERS =====
|
||||
# Speed ranges: [0-35, 35-55, 55-70, 70+ mph]
|
||||
SPEED_BREAKPOINTS = [0, 35, 55, 70]
|
||||
|
||||
# [City, Urban Hwy, Rural Hwy, High Speed]
|
||||
X_EGO_OBSTACLE_COSTS = [3.0, 3.0, 2.5, 2.0]
|
||||
J_EGO_COSTS = [5.0, 4.75, 4.5, 4.0]
|
||||
A_CHANGE_COSTS = [200.0, 195.0, 180.0, 170.0]
|
||||
LEAD_FILTER_TIME_LOW = 0.8
|
||||
LEAD_FILTER_TIME_HIGH = 1.2
|
||||
DIST_ADAPTS = [0.04, 0.06, 0.06, 0.05]
|
||||
|
||||
# Current active values
|
||||
X_EGO_OBSTACLE_COST = 2.75
|
||||
X_EGO_COST = 0.
|
||||
V_EGO_COST = 0.
|
||||
A_EGO_COST = 0.
|
||||
J_EGO_COST = 5.0
|
||||
A_CHANGE_COST = 200.
|
||||
J_EGO_COST = 5.5
|
||||
A_CHANGE_COST = 250.0
|
||||
DANGER_ZONE_COST = 100.
|
||||
CRASH_DISTANCE = .25
|
||||
LEAD_DANGER_FACTOR = 0.75
|
||||
@@ -58,6 +80,11 @@ STOP_DISTANCE = 6.0
|
||||
CRUISE_MIN_ACCEL = -1.2
|
||||
CRUISE_MAX_ACCEL = 1.6
|
||||
|
||||
|
||||
def get_speed_based_param(speed_mph, param_array):
|
||||
return float(np.interp(speed_mph, SPEED_BREAKPOINTS, param_array))
|
||||
|
||||
|
||||
def get_jerk_factor(aggressive_jerk_acceleration=0.5, aggressive_jerk_danger=0.5, aggressive_jerk_speed=0.5,
|
||||
standard_jerk_acceleration=1.0, standard_jerk_danger=1.0, standard_jerk_speed=1.0,
|
||||
relaxed_jerk_acceleration=1.0, relaxed_jerk_danger=1.0, relaxed_jerk_speed=1.0,
|
||||
@@ -105,13 +132,15 @@ def get_T_FOLLOW(aggressive_follow=1.25, standard_follow=1.45, relaxed_follow=1.
|
||||
def get_stopped_equivalence_factor(v_lead):
|
||||
return (v_lead**2) / (2 * COMFORT_BRAKE)
|
||||
|
||||
def get_safe_obstacle_distance(v_ego, t_follow):
|
||||
return (v_ego**2) / (2 * COMFORT_BRAKE) + t_follow * v_ego + STOP_DISTANCE
|
||||
|
||||
def desired_follow_distance(v_ego, v_lead, t_follow=None):
|
||||
def get_safe_obstacle_distance(v_ego, t_follow, stop_distance=STOP_DISTANCE):
|
||||
return (v_ego**2) / (2 * COMFORT_BRAKE) + t_follow * v_ego + stop_distance
|
||||
|
||||
|
||||
def desired_follow_distance(v_ego, v_lead, t_follow=None, stop_distance=STOP_DISTANCE):
|
||||
if t_follow is None:
|
||||
t_follow = get_T_FOLLOW()
|
||||
return get_safe_obstacle_distance(v_ego, t_follow) - get_stopped_equivalence_factor(v_lead)
|
||||
return get_safe_obstacle_distance(v_ego, t_follow, stop_distance) - get_stopped_equivalence_factor(v_lead)
|
||||
|
||||
|
||||
def gen_long_model():
|
||||
@@ -249,9 +278,27 @@ class LongitudinalMpc:
|
||||
self.mode = mode
|
||||
self.dt = dt
|
||||
self.solver = AcadosOcpSolverCython(MODEL_NAME, ACADOS_SOLVER_TYPE, N)
|
||||
self.reset()
|
||||
self.source = SOURCES[2]
|
||||
|
||||
self.current_filter_time = LEAD_FILTER_TIME_LOW
|
||||
self.prev_filter_time = self.current_filter_time
|
||||
self.lead_a_filter = FirstOrderFilter(0.0, self.current_filter_time, self.dt)
|
||||
self.lead_v_filter = FirstOrderFilter(0.0, self.current_filter_time, self.dt)
|
||||
self.filter_time_factor = 1.0
|
||||
self.prev_filter_time_factor = 1.0
|
||||
self.slew_per_sec = 1.0
|
||||
|
||||
self.current_x_ego_cost = X_EGO_OBSTACLE_COSTS[0]
|
||||
self.current_j_ego_cost = J_EGO_COSTS[0]
|
||||
self.current_a_change_cost = A_CHANGE_COSTS[0]
|
||||
self.current_dist_adapt = DIST_ADAPTS[0]
|
||||
|
||||
self.cruise_min_a = ACCEL_MIN
|
||||
self.max_a = min(ACCEL_MAX, 1.2)
|
||||
self.stop_distance = STOP_DISTANCE
|
||||
|
||||
self.reset()
|
||||
|
||||
def reset(self):
|
||||
# self.solver = AcadosOcpSolverCython(MODEL_NAME, ACADOS_SOLVER_TYPE, N)
|
||||
self.solver.reset()
|
||||
@@ -297,10 +344,56 @@ class LongitudinalMpc:
|
||||
for i in range(N):
|
||||
self.solver.cost_set(i, 'Zl', Zl)
|
||||
|
||||
def set_weights(self, acceleration_jerk=1.0, danger_jerk=1.0, speed_jerk=1.0, prev_accel_constraint=True, personality=log.LongitudinalPersonality.standard):
|
||||
def set_weights(self, acceleration_jerk=1.0, danger_jerk=1.0, speed_jerk=1.0, prev_accel_constraint=True,
|
||||
personality=log.LongitudinalPersonality.standard, v_ego=0.0, lead_dist=50.0,
|
||||
uncertainty=0.0, accel_reengage=False, panic_bypass=False, stop_distance=STOP_DISTANCE):
|
||||
self.stop_distance = max(float(stop_distance), 4.0)
|
||||
|
||||
speed_mph = v_ego * CV.MS_TO_MPH
|
||||
self.current_x_ego_cost = get_speed_based_param(speed_mph, X_EGO_OBSTACLE_COSTS)
|
||||
self.current_j_ego_cost = get_speed_based_param(speed_mph, J_EGO_COSTS)
|
||||
self.current_a_change_cost = get_speed_based_param(speed_mph, A_CHANGE_COSTS)
|
||||
|
||||
dist_adapt_array = [0.0, DIST_ADAPTS[1], DIST_ADAPTS[2], DIST_ADAPTS[3]]
|
||||
self.current_dist_adapt = get_speed_based_param(speed_mph, dist_adapt_array)
|
||||
|
||||
if speed_mph < 47:
|
||||
self.current_filter_time = 0.0
|
||||
else:
|
||||
self.current_filter_time = float(np.interp(speed_mph, [47, 65], [0.0, LEAD_FILTER_TIME_HIGH]))
|
||||
|
||||
if abs(self.current_filter_time - self.prev_filter_time) > 0.1:
|
||||
self.lead_a_filter = FirstOrderFilter(self.lead_a_filter.x, self.current_filter_time, self.dt)
|
||||
self.lead_v_filter = FirstOrderFilter(self.lead_v_filter.x, self.current_filter_time, self.dt)
|
||||
self.prev_filter_time = self.current_filter_time
|
||||
|
||||
dist_factor = 1.0 + self.current_dist_adapt * (20.0 / max(lead_dist, 5.0))
|
||||
acceleration_jerk *= dist_factor
|
||||
danger_jerk *= dist_factor
|
||||
speed_jerk *= dist_factor
|
||||
|
||||
if uncertainty <= 0.45:
|
||||
tgt_factor = 1.0
|
||||
elif uncertainty >= 0.70:
|
||||
tgt_factor = 0.0
|
||||
else:
|
||||
tgt_factor = float(np.interp(uncertainty, [0.45, 0.70], [1.0, 0.30]))
|
||||
|
||||
if accel_reengage:
|
||||
tgt_factor = min(tgt_factor, 0.5)
|
||||
if panic_bypass:
|
||||
tgt_factor = 0.0
|
||||
|
||||
max_step = self.slew_per_sec * self.dt
|
||||
delta = np.clip(tgt_factor - self.filter_time_factor, -max_step, max_step)
|
||||
self.filter_time_factor += float(delta)
|
||||
|
||||
if 0.45 <= uncertainty < 0.60:
|
||||
speed_jerk *= float(np.interp(uncertainty, [0.45, 0.60], [1.2, 1.5]))
|
||||
|
||||
if self.mode == 'acc':
|
||||
a_change_cost = acceleration_jerk if prev_accel_constraint else 0
|
||||
cost_weights = [X_EGO_OBSTACLE_COST, X_EGO_COST, V_EGO_COST, A_EGO_COST, a_change_cost, speed_jerk]
|
||||
cost_weights = [self.current_x_ego_cost, X_EGO_COST, V_EGO_COST, A_EGO_COST, a_change_cost, speed_jerk]
|
||||
constraint_cost_weights = [LIMIT_COST, LIMIT_COST, LIMIT_COST, danger_jerk]
|
||||
elif self.mode == 'blended':
|
||||
a_change_cost = 40.0 if prev_accel_constraint else 0
|
||||
@@ -310,6 +403,12 @@ class LongitudinalMpc:
|
||||
raise NotImplementedError(f'Planner mode {self.mode} not recognized in planner cost set')
|
||||
self.set_cost_weights(cost_weights, constraint_cost_weights)
|
||||
|
||||
if abs(self.filter_time_factor - self.prev_filter_time_factor) > 0.05:
|
||||
new_filter_time = self.current_filter_time * self.filter_time_factor
|
||||
self.lead_a_filter = FirstOrderFilter(self.lead_a_filter.x, new_filter_time, self.dt)
|
||||
self.lead_v_filter = FirstOrderFilter(self.lead_v_filter.x, new_filter_time, self.dt)
|
||||
self.prev_filter_time_factor = self.filter_time_factor
|
||||
|
||||
def set_cur_state(self, v, a):
|
||||
v_prev = self.x0[1]
|
||||
self.x0[1] = v
|
||||
@@ -319,22 +418,35 @@ class LongitudinalMpc:
|
||||
self.solver.set(i, 'x', self.x0)
|
||||
|
||||
@staticmethod
|
||||
def extrapolate_lead(x_lead, v_lead, a_lead, a_lead_tau):
|
||||
a_lead_traj = a_lead * np.exp(-a_lead_tau * (T_IDXS**2)/2.)
|
||||
v_lead_traj = np.clip(v_lead + np.cumsum(T_DIFFS * a_lead_traj), 0.0, 1e8)
|
||||
x_lead_traj = x_lead + np.cumsum(T_DIFFS * v_lead_traj)
|
||||
def extrapolate_lead(x_lead, v_lead, a_lead, a_lead_tau, v_ego=0.0):
|
||||
speed_mph = v_ego * CV.MS_TO_MPH
|
||||
exp_weight = float(np.interp(speed_mph, [0, 20, 35], [1.0, 1.0, 0.0]))
|
||||
|
||||
if exp_weight > 0.0:
|
||||
a_lead_traj_exp = a_lead * np.exp(-a_lead_tau * (T_IDXS**2)/2.)
|
||||
v_lead_traj_exp = np.clip(v_lead + np.cumsum(T_DIFFS * a_lead_traj_exp), 0.0, 1e8)
|
||||
x_lead_traj_exp = x_lead + np.cumsum(T_DIFFS * v_lead_traj_exp)
|
||||
else:
|
||||
x_lead_traj_exp = np.zeros_like(T_IDXS)
|
||||
v_lead_traj_exp = np.zeros_like(T_IDXS)
|
||||
|
||||
v_lead_traj_const = np.clip(v_lead + a_lead * T_IDXS, 0.0, 1e8)
|
||||
x_lead_traj_const = x_lead + v_lead * T_IDXS + 0.5 * a_lead * T_IDXS**2
|
||||
|
||||
v_lead_traj = exp_weight * v_lead_traj_exp + (1.0 - exp_weight) * v_lead_traj_const
|
||||
x_lead_traj = exp_weight * x_lead_traj_exp + (1.0 - exp_weight) * x_lead_traj_const
|
||||
|
||||
lead_xv = np.column_stack((x_lead_traj, v_lead_traj))
|
||||
return lead_xv
|
||||
|
||||
def process_lead(self, lead):
|
||||
def process_lead(self, lead, tracking_lead=True):
|
||||
v_ego = self.x0[1]
|
||||
if lead is not None and lead.status:
|
||||
if lead is not None and lead.status and tracking_lead:
|
||||
x_lead = lead.dRel
|
||||
v_lead = lead.vLead
|
||||
a_lead = lead.aLeadK
|
||||
a_lead_tau = lead.aLeadTau
|
||||
else:
|
||||
# Fake a fast lead car, so mpc can keep running in the same mode
|
||||
x_lead = 50.0
|
||||
v_lead = v_ego + 10.0
|
||||
a_lead = 0.0
|
||||
@@ -346,15 +458,25 @@ class LongitudinalMpc:
|
||||
x_lead = np.clip(x_lead, min_x_lead, 1e8)
|
||||
v_lead = np.clip(v_lead, 0.0, 1e8)
|
||||
a_lead = np.clip(a_lead, -10., 5.)
|
||||
lead_xv = self.extrapolate_lead(x_lead, v_lead, a_lead, a_lead_tau)
|
||||
|
||||
self.lead_a_filter.update(a_lead)
|
||||
self.lead_v_filter.update(v_lead)
|
||||
lead_xv = self.extrapolate_lead(x_lead, self.lead_v_filter.x, self.lead_a_filter.x, a_lead_tau, v_ego)
|
||||
return lead_xv
|
||||
|
||||
def update(self, radarstate, v_cruise, x, v, a, j, danger_factor, t_follow, personality=log.LongitudinalPersonality.standard):
|
||||
v_ego = self.x0[1]
|
||||
self.status = radarstate.leadOne.status or radarstate.leadTwo.status
|
||||
def set_accel_limits(self, min_a, max_a):
|
||||
self.cruise_min_a = min_a
|
||||
self.max_a = max_a
|
||||
|
||||
lead_xv_0 = self.process_lead(radarstate.leadOne)
|
||||
lead_xv_1 = self.process_lead(radarstate.leadTwo)
|
||||
def update(self, radarstate, v_cruise, x, v, a, j, danger_factor, t_follow,
|
||||
personality=log.LongitudinalPersonality.standard, tracking_lead=True):
|
||||
v_ego = self.x0[1]
|
||||
lead_one = radarstate.leadOne
|
||||
lead_two = radarstate.leadTwo
|
||||
self.status = (lead_one.status and tracking_lead) or lead_two.status
|
||||
|
||||
lead_xv_0 = self.process_lead(lead_one, tracking_lead)
|
||||
lead_xv_1 = self.process_lead(lead_two, True)
|
||||
|
||||
# To estimate a safe distance from a moving lead, we calculate how much stopping
|
||||
# distance that lead needs as a minimum. We can add that to the current distance
|
||||
@@ -363,7 +485,7 @@ class LongitudinalMpc:
|
||||
lead_1_obstacle = lead_xv_1[:,0] + get_stopped_equivalence_factor(lead_xv_1[:,1])
|
||||
|
||||
self.params[:,0] = ACCEL_MIN
|
||||
self.params[:,1] = ACCEL_MAX
|
||||
self.params[:,1] = max(0.0, self.max_a)
|
||||
|
||||
# Update in ACC mode or ACC/e2e blend
|
||||
if self.mode == 'acc':
|
||||
@@ -371,13 +493,13 @@ class LongitudinalMpc:
|
||||
|
||||
# Fake an obstacle for cruise, this ensures smooth acceleration to set speed
|
||||
# when the leads are no factor.
|
||||
v_lower = v_ego + (T_IDXS * CRUISE_MIN_ACCEL * 1.05)
|
||||
v_lower = v_ego + (T_IDXS * self.cruise_min_a * 1.05)
|
||||
# TODO does this make sense when max_a is negative?
|
||||
v_upper = v_ego + (T_IDXS * CRUISE_MAX_ACCEL * 1.05)
|
||||
v_upper = v_ego + (T_IDXS * self.max_a * 1.05)
|
||||
v_cruise_clipped = np.clip(v_cruise * np.ones(N+1),
|
||||
v_lower,
|
||||
v_upper)
|
||||
cruise_obstacle = np.cumsum(T_DIFFS * v_cruise_clipped) + get_safe_obstacle_distance(v_cruise_clipped, t_follow)
|
||||
cruise_obstacle = np.cumsum(T_DIFFS * v_cruise_clipped) + get_safe_obstacle_distance(v_cruise_clipped, t_follow, self.stop_distance)
|
||||
x_obstacles = np.column_stack([lead_0_obstacle, lead_1_obstacle, cruise_obstacle])
|
||||
self.source = SOURCES[np.argmin(x_obstacles[0])]
|
||||
|
||||
@@ -415,7 +537,7 @@ class LongitudinalMpc:
|
||||
|
||||
self.run()
|
||||
if (np.any(lead_xv_0[FCW_IDXS,0] - self.x_sol[FCW_IDXS,0] < CRASH_DISTANCE) and
|
||||
radarstate.leadOne.modelProb > 0.9):
|
||||
lead_one.modelProb > 0.9):
|
||||
self.crash_cnt += 1
|
||||
else:
|
||||
self.crash_cnt = 0
|
||||
@@ -423,9 +545,9 @@ class LongitudinalMpc:
|
||||
# Check if it got within lead comfort range
|
||||
# TODO This should be done cleaner
|
||||
if self.mode == 'blended':
|
||||
if any((lead_0_obstacle - get_safe_obstacle_distance(self.x_sol[:,1], t_follow))- self.x_sol[:,0] < 0.0):
|
||||
if any((lead_0_obstacle - get_safe_obstacle_distance(self.x_sol[:,1], t_follow, self.stop_distance))- self.x_sol[:,0] < 0.0):
|
||||
self.source = 'lead0'
|
||||
if any((lead_1_obstacle - get_safe_obstacle_distance(self.x_sol[:,1], t_follow))- self.x_sol[:,0] < 0.0) and \
|
||||
if any((lead_1_obstacle - get_safe_obstacle_distance(self.x_sol[:,1], t_follow, self.stop_distance))- self.x_sol[:,0] < 0.0) and \
|
||||
(lead_1_obstacle[0] - lead_0_obstacle[0]):
|
||||
self.source = 'lead1'
|
||||
|
||||
|
||||
@@ -1,5 +1,6 @@
|
||||
#!/usr/bin/env python3
|
||||
import math
|
||||
import time
|
||||
import numpy as np
|
||||
|
||||
import cereal.messaging as messaging
|
||||
@@ -12,7 +13,7 @@ from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState
|
||||
from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import LongitudinalMpc
|
||||
from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import T_IDXS as T_IDXS_MPC
|
||||
from openpilot.selfdrive.controls.lib.drive_helpers import CONTROL_N, get_accel_from_plan
|
||||
from openpilot.selfdrive.car.cruise import V_CRUISE_MAX, V_CRUISE_UNSET
|
||||
from openpilot.selfdrive.car.cruise import V_CRUISE_UNSET
|
||||
from openpilot.common.swaglog import cloudlog
|
||||
|
||||
from openpilot.frogpilot.common.frogpilot_variables import MINIMUM_LATERAL_ACCELERATION
|
||||
@@ -24,6 +25,10 @@ CONTROL_N_T_IDX = ModelConstants.T_IDXS[:CONTROL_N]
|
||||
ALLOW_THROTTLE_THRESHOLD = 0.4
|
||||
MIN_ALLOW_THROTTLE_SPEED = 2.5
|
||||
|
||||
# Uncertainty-based filter disable thresholds
|
||||
UNCERT_SLOPE_TRIG = 0.12 # per second
|
||||
UNCERT_MAG_TRIG = 0.50
|
||||
|
||||
# Lookup table for turns
|
||||
_A_TOTAL_MAX_V = [1.7, 3.2]
|
||||
_A_TOTAL_MAX_BP = [20., 40.]
|
||||
@@ -58,11 +63,11 @@ class LongitudinalPlanner:
|
||||
def __init__(self, CP, init_v=0.0, init_a=0.0, dt=DT_MDL):
|
||||
self.CP = CP
|
||||
self.mpc = LongitudinalMpc(dt=dt)
|
||||
# TODO remove mpc modes when TR released
|
||||
self.mpc.mode = 'acc'
|
||||
self.fcw = False
|
||||
self.dt = dt
|
||||
self.allow_throttle = True
|
||||
self.mode = 'acc'
|
||||
self.generation = None
|
||||
|
||||
self.a_desired = init_a
|
||||
self.v_desired_filter = FirstOrderFilter(init_v, 2.0, self.dt)
|
||||
@@ -75,13 +80,32 @@ class LongitudinalPlanner:
|
||||
self.j_desired_trajectory = np.zeros(CONTROL_N)
|
||||
self.solverExecutionTime = 0.0
|
||||
|
||||
self.uncert_slow = FirstOrderFilter(0.0, 1.6, self.dt)
|
||||
self.uncert_fast = FirstOrderFilter(0.0, 0.9, self.dt)
|
||||
self.prev_lead_dist = None
|
||||
self.last_big_brake_t = 0.0
|
||||
self.stable_lead = False
|
||||
self.lead_dist_f = None
|
||||
self._uncert_last = 0.0
|
||||
self._uncert_last_t = None
|
||||
|
||||
@property
|
||||
def mlsim(self):
|
||||
return self.generation in ("v8", "v10", "v11", "v12")
|
||||
|
||||
@staticmethod
|
||||
def parse_model(model_msg, v_ego, frogpilot_toggles):
|
||||
def get_model_speed_error(model_msg, v_ego):
|
||||
if len(model_msg.velocity.x) == ModelConstants.IDX_N:
|
||||
return float(np.clip(model_msg.velocity.x[0] - v_ego, -5.0, 5.0))
|
||||
return 0.0
|
||||
|
||||
@staticmethod
|
||||
def parse_model(model_msg, model_error, v_ego, frogpilot_toggles):
|
||||
if (len(model_msg.position.x) == ModelConstants.IDX_N and
|
||||
len(model_msg.velocity.x) == ModelConstants.IDX_N and
|
||||
len(model_msg.acceleration.x) == ModelConstants.IDX_N):
|
||||
x = np.interp(T_IDXS_MPC, ModelConstants.T_IDXS, model_msg.position.x)
|
||||
v = np.interp(T_IDXS_MPC, ModelConstants.T_IDXS, model_msg.velocity.x)
|
||||
x = np.interp(T_IDXS_MPC, ModelConstants.T_IDXS, model_msg.position.x) - model_error * T_IDXS_MPC
|
||||
v = np.interp(T_IDXS_MPC, ModelConstants.T_IDXS, model_msg.velocity.x) - model_error
|
||||
a = np.interp(T_IDXS_MPC, ModelConstants.T_IDXS, model_msg.acceleration.x)
|
||||
j = np.zeros(len(T_IDXS_MPC))
|
||||
else:
|
||||
@@ -104,14 +128,18 @@ class LongitudinalPlanner:
|
||||
return x, v, a, j, throttle_prob
|
||||
|
||||
def update(self, sm, frogpilot_toggles):
|
||||
mode = 'blended' if sm['selfdriveState'].experimentalMode else 'acc'
|
||||
self.generation = getattr(frogpilot_toggles, "model_version", None)
|
||||
self.mode = 'blended' if sm['selfdriveState'].experimentalMode else 'acc'
|
||||
self.mpc.mode = 'acc'
|
||||
if not self.mlsim:
|
||||
self.mpc.mode = self.mode
|
||||
|
||||
if len(sm['carControl'].orientationNED) == 3:
|
||||
accel_coast = get_coast_accel(sm['carControl'].orientationNED[1])
|
||||
else:
|
||||
accel_coast = ACCEL_MAX
|
||||
|
||||
v_ego = sm['carState'].vEgo
|
||||
v_ego = max(sm['carState'].vEgo, sm['carState'].vEgoCluster)
|
||||
v_cruise = sm['frogpilotPlan'].vCruise
|
||||
v_cruise_initialized = sm['carState'].vCruise != V_CRUISE_UNSET
|
||||
|
||||
@@ -126,7 +154,7 @@ class LongitudinalPlanner:
|
||||
# No change cost when user is controlling the speed, or when standstill
|
||||
prev_accel_constraint = not (reset_state or sm['carState'].standstill)
|
||||
|
||||
if mode == 'acc':
|
||||
if self.mpc.mode == 'acc':
|
||||
accel_clip = [sm['frogpilotPlan'].minAcceleration, sm['frogpilotPlan'].maxAcceleration]
|
||||
steer_angle_without_offset = sm['carState'].steeringAngleDeg - sm['liveParameters'].angleOffsetDeg
|
||||
if not sm['frogpilotPlan'].cscControllingSpeed:
|
||||
@@ -141,9 +169,11 @@ class LongitudinalPlanner:
|
||||
|
||||
# Prevent divergence, smooth in current v_ego
|
||||
self.v_desired_filter.x = max(0.0, self.v_desired_filter.update(v_ego))
|
||||
x, v, a, j, throttle_prob = self.parse_model(sm['modelV2'], v_ego, frogpilot_toggles)
|
||||
model_error = self.get_model_speed_error(sm['modelV2'], v_ego)
|
||||
x, v, a, j, throttle_prob = self.parse_model(sm['modelV2'], model_error, v_ego, frogpilot_toggles)
|
||||
# Don't clip at low speeds since throttle_prob doesn't account for creep
|
||||
self.allow_throttle = throttle_prob > ALLOW_THROTTLE_THRESHOLD or v_ego <= MIN_ALLOW_THROTTLE_SPEED
|
||||
self.allow_throttle &= not sm['frogpilotPlan'].disableThrottle
|
||||
|
||||
if not self.allow_throttle:
|
||||
clipped_accel_coast = max(accel_coast, accel_clip[0])
|
||||
@@ -153,9 +183,99 @@ class LongitudinalPlanner:
|
||||
if force_slow_decel:
|
||||
v_cruise = 0.0
|
||||
|
||||
self.mpc.set_weights(sm['frogpilotPlan'].accelerationJerk, sm['frogpilotPlan'].dangerJerk, sm['frogpilotPlan'].speedJerk, prev_accel_constraint, personality=sm['selfdriveState'].personality)
|
||||
accel_clip[0] = min(accel_clip[0], self.a_desired + 0.05)
|
||||
accel_clip[1] = max(accel_clip[1], self.a_desired - 0.05)
|
||||
|
||||
lead_one = sm['radarState'].leadOne
|
||||
lead_dist = lead_one.dRel if lead_one.status else 50.0
|
||||
|
||||
alpha = max(0.02, min(0.15, 0.05 + 0.002 * v_ego))
|
||||
if self.lead_dist_f is None:
|
||||
self.lead_dist_f = float(lead_dist)
|
||||
else:
|
||||
self.lead_dist_f += alpha * (float(lead_dist) - self.lead_dist_f)
|
||||
|
||||
now_t = time.monotonic()
|
||||
v_rel = (v_ego - lead_one.vLead) if lead_one.status else 0.0
|
||||
if self.prev_lead_dist is None:
|
||||
d_rel_dot = 0.0
|
||||
else:
|
||||
d_rel_dot = (lead_dist - self.prev_lead_dist) / max(self.dt, 1e-3)
|
||||
self.prev_lead_dist = lead_dist
|
||||
|
||||
uncertainty = 0.0
|
||||
raw_brake_max = 0.0
|
||||
if hasattr(sm['modelV2'], 'meta'):
|
||||
desire_entropy = 0.0
|
||||
if hasattr(sm['modelV2'].meta, 'desirePrediction'):
|
||||
desire_probs = sm['modelV2'].meta.desirePrediction
|
||||
if len(desire_probs) > 1:
|
||||
probs = np.asarray(desire_probs, dtype=float)
|
||||
total = float(np.sum(probs))
|
||||
if total > 1e-6:
|
||||
p = probs / total
|
||||
entropy = -np.sum(p * np.log(p + 1e-10))
|
||||
max_entropy = np.log(len(p))
|
||||
desire_entropy = float(entropy / max(max_entropy, 1e-6))
|
||||
|
||||
disengage_risk = 0.0
|
||||
if hasattr(sm['modelV2'].meta, 'disengagePredictions'):
|
||||
brake_probs = sm['modelV2'].meta.disengagePredictions.brakePressProbs
|
||||
if len(brake_probs) > 0:
|
||||
probs = np.asarray(brake_probs, dtype=float)
|
||||
if float(np.max(probs)) < 0.015:
|
||||
probs = probs * 0.5
|
||||
raw_brake_max = float(np.max(probs))
|
||||
t = np.arange(len(probs), dtype=float) * DT_MDL
|
||||
lam = 0.6
|
||||
weights = np.exp(-lam * t)
|
||||
disengage_risk = float(np.max(probs * weights))
|
||||
|
||||
raw_uncertainty = desire_entropy + disengage_risk
|
||||
self.uncert_slow.update(raw_uncertainty)
|
||||
self.uncert_fast.update(raw_uncertainty)
|
||||
uncertainty = self.uncert_slow.x
|
||||
|
||||
if raw_brake_max > 0.02:
|
||||
self.last_big_brake_t = now_t
|
||||
|
||||
recently_braked = (now_t - self.last_big_brake_t) < 0.7
|
||||
self.stable_lead = (
|
||||
lead_one.status and
|
||||
abs(v_rel) < 0.5 and
|
||||
abs(d_rel_dot) < 0.5 and
|
||||
not recently_braked
|
||||
)
|
||||
|
||||
if self._uncert_last_t is None:
|
||||
uncert_slope = 0.0
|
||||
else:
|
||||
dt_u = max(1e-3, now_t - self._uncert_last_t)
|
||||
uncert_slope = (uncertainty - self._uncert_last) / dt_u
|
||||
self._uncert_last = uncertainty
|
||||
self._uncert_last_t = now_t
|
||||
|
||||
closing_fast = lead_one.status and (v_ego - lead_one.vLead) > 0.5
|
||||
panic_bypass = closing_fast and (uncert_slope > UNCERT_SLOPE_TRIG or uncertainty >= UNCERT_MAG_TRIG)
|
||||
if panic_bypass:
|
||||
cloudlog.error(f"LON_SLOPE slope={uncert_slope:.3f} uncertainty={uncertainty:.3f} v_ego={v_ego:.2f}")
|
||||
|
||||
self.mpc.set_weights(sm['frogpilotPlan'].accelerationJerk,
|
||||
sm['frogpilotPlan'].dangerJerk,
|
||||
sm['frogpilotPlan'].speedJerk,
|
||||
prev_accel_constraint,
|
||||
personality=sm['selfdriveState'].personality,
|
||||
v_ego=v_ego,
|
||||
lead_dist=self.lead_dist_f if self.lead_dist_f is not None else lead_dist,
|
||||
uncertainty=uncertainty,
|
||||
panic_bypass=panic_bypass,
|
||||
stop_distance=getattr(frogpilot_toggles, "stop_distance", 6.0))
|
||||
self.mpc.set_accel_limits(accel_clip[0], accel_clip[1])
|
||||
self.mpc.set_cur_state(self.v_desired_filter.x, self.a_desired)
|
||||
self.mpc.update(sm['radarState'], v_cruise, x, v, a, j, sm['frogpilotPlan'].dangerFactor, sm['frogpilotPlan'].tFollow, personality=sm['selfdriveState'].personality)
|
||||
tracking_lead = sm['frogpilotPlan'].desiredFollowDistance > 0
|
||||
self.mpc.update(sm['radarState'], v_cruise, x, v, a, j,
|
||||
sm['frogpilotPlan'].dangerFactor, sm['frogpilotPlan'].tFollow,
|
||||
personality=sm['selfdriveState'].personality, tracking_lead=tracking_lead)
|
||||
|
||||
self.v_desired_trajectory = np.interp(CONTROL_N_T_IDX, T_IDXS_MPC, self.mpc.v_solution)
|
||||
self.a_desired_trajectory = np.interp(CONTROL_N_T_IDX, T_IDXS_MPC, self.mpc.a_solution)
|
||||
@@ -171,13 +291,27 @@ class LongitudinalPlanner:
|
||||
self.a_desired = float(np.interp(self.dt, CONTROL_N_T_IDX, self.a_desired_trajectory))
|
||||
self.v_desired_filter.x = self.v_desired_filter.x + self.dt * (self.a_desired + a_prev) / 2.0
|
||||
|
||||
if lead_one.status:
|
||||
rel_v = max(0.0, v_ego - lead_one.vLead)
|
||||
base_th = 1.6
|
||||
th = base_th + 0.6 * max(0.0, uncertainty - 0.42)
|
||||
desired_gap = th * v_ego
|
||||
if self.lead_dist_f is not None and self.lead_dist_f < desired_gap and rel_v > 0.5:
|
||||
k_rel, k_unc = 0.04, 0.20
|
||||
pre_brake = k_rel * rel_v + k_unc * max(0.0, uncertainty - 0.42)
|
||||
self.a_desired = float(self.a_desired - min(pre_brake, 0.06))
|
||||
|
||||
if -0.05 < self.a_desired < 0.05:
|
||||
self.a_desired = 0.0
|
||||
|
||||
action_t = frogpilot_toggles.longitudinalActuatorDelay + DT_MDL
|
||||
output_a_target_mpc, output_should_stop_mpc = get_accel_from_plan(self.v_desired_trajectory, self.a_desired_trajectory, CONTROL_N_T_IDX,
|
||||
action_t=action_t, vEgoStopping=frogpilot_toggles.vEgoStopping)
|
||||
output_a_target_e2e = sm['modelV2'].action.desiredAcceleration
|
||||
output_should_stop_e2e = sm['modelV2'].action.shouldStop
|
||||
|
||||
if mode == 'acc':
|
||||
# Keep StarPilot behavior: for tinygrad v10/v11/v12 in experimental mode, blend with model action output.
|
||||
if self.mode == 'acc' or self.generation == 'v9':
|
||||
output_a_target = output_a_target_mpc
|
||||
self.output_should_stop = output_should_stop_mpc
|
||||
else:
|
||||
@@ -208,7 +342,7 @@ class LongitudinalPlanner:
|
||||
longitudinalPlan.fcw = self.fcw
|
||||
|
||||
longitudinalPlan.aTarget = float(self.output_a_target)
|
||||
longitudinalPlan.shouldStop = bool(self.output_should_stop)
|
||||
longitudinalPlan.shouldStop = bool(self.output_should_stop) or sm['frogpilotPlan'].forcingStopLength < 1
|
||||
longitudinalPlan.allowBrake = True
|
||||
longitudinalPlan.allowThrottle = bool(self.allow_throttle)
|
||||
|
||||
|
||||
@@ -1,4 +1,5 @@
|
||||
from parameterized import parameterized
|
||||
from types import SimpleNamespace
|
||||
|
||||
from cereal import car, log
|
||||
from opendbc.car.car_helpers import interfaces
|
||||
@@ -16,7 +17,7 @@ from openpilot.selfdrive.controls.lib.latcontrol_angle import LatControlAngle
|
||||
class TestLatControl:
|
||||
|
||||
@parameterized.expand([(HONDA.HONDA_CIVIC, LatControlPID), (TOYOTA.TOYOTA_RAV4, LatControlTorque),
|
||||
(NISSAN.NISSAN_LEAF, LatControlAngle), (GM.CHEVROLET_BOLT_EUV, LatControlTorque)])
|
||||
(NISSAN.NISSAN_LEAF, LatControlAngle), (GM.CHEVROLET_BOLT_ACC_2022_2023, LatControlTorque)])
|
||||
def test_saturation(self, car_name, controller):
|
||||
CarInterface = interfaces[car_name]
|
||||
CP = CarInterface.get_non_essential_params(car_name)
|
||||
@@ -30,16 +31,17 @@ class TestLatControl:
|
||||
CS.steeringPressed = False
|
||||
|
||||
params = log.LiveParametersData.new_message()
|
||||
frogpilot_toggles = SimpleNamespace()
|
||||
|
||||
# Saturate for curvature limited and controller limited
|
||||
for _ in range(1000):
|
||||
_, _, lac_log = controller.update(True, CS, VM, params, False, 0, True, 0.2)
|
||||
_, _, lac_log = controller.update(True, CS, VM, params, False, 0, True, 0.2, None, None, frogpilot_toggles)
|
||||
assert lac_log.saturated
|
||||
|
||||
for _ in range(1000):
|
||||
_, _, lac_log = controller.update(True, CS, VM, params, False, 0, False, 0.2)
|
||||
_, _, lac_log = controller.update(True, CS, VM, params, False, 0, False, 0.2, None, None, frogpilot_toggles)
|
||||
assert not lac_log.saturated
|
||||
|
||||
for _ in range(1000):
|
||||
_, _, lac_log = controller.update(True, CS, VM, params, False, 1, False, 0.2)
|
||||
_, _, lac_log = controller.update(True, CS, VM, params, False, 1, False, 0.2, None, None, frogpilot_toggles)
|
||||
assert lac_log.saturated
|
||||
|
||||
@@ -0,0 +1,66 @@
|
||||
#!/usr/bin/env python3
|
||||
import argparse
|
||||
import time
|
||||
|
||||
from cereal import log, messaging
|
||||
from openpilot.system.hardware import HARDWARE
|
||||
|
||||
NETWORK_TYPES = {
|
||||
"none": log.DeviceState.NetworkType.none,
|
||||
"wifi": log.DeviceState.NetworkType.wifi,
|
||||
"ethernet": log.DeviceState.NetworkType.ethernet,
|
||||
"cell2G": log.DeviceState.NetworkType.cell2G,
|
||||
"cell3G": log.DeviceState.NetworkType.cell3G,
|
||||
"cell4G": log.DeviceState.NetworkType.cell4G,
|
||||
"cell5G": log.DeviceState.NetworkType.cell5G,
|
||||
}
|
||||
|
||||
NETWORK_STRENGTHS = {
|
||||
"unknown": log.DeviceState.NetworkStrength.unknown,
|
||||
"poor": log.DeviceState.NetworkStrength.poor,
|
||||
"moderate": log.DeviceState.NetworkStrength.moderate,
|
||||
"good": log.DeviceState.NetworkStrength.good,
|
||||
"great": log.DeviceState.NetworkStrength.great,
|
||||
}
|
||||
|
||||
|
||||
def parse_args() -> argparse.Namespace:
|
||||
parser = argparse.ArgumentParser(description="Publish fake deviceState network info for desktop UI demos.")
|
||||
parser.add_argument("--network", choices=NETWORK_TYPES.keys(), default="wifi", help="network type to publish")
|
||||
parser.add_argument("--strength", choices=NETWORK_STRENGTHS.keys(), default="great", help="network strength to publish")
|
||||
parser.add_argument("--started", action="store_true", help="publish started=true (onroad)")
|
||||
parser.add_argument("--metered", action="store_true", help="publish networkMetered=true")
|
||||
parser.add_argument("--interval", type=float, default=0.2, help="publish interval in seconds")
|
||||
return parser.parse_args()
|
||||
|
||||
|
||||
def main() -> None:
|
||||
args = parse_args()
|
||||
|
||||
pm = messaging.PubMaster(["deviceState"])
|
||||
interval = max(args.interval, 0.05)
|
||||
network_type = NETWORK_TYPES[args.network]
|
||||
network_strength = NETWORK_STRENGTHS[args.strength]
|
||||
|
||||
while True:
|
||||
msg = messaging.new_message("deviceState")
|
||||
ds = msg.deviceState
|
||||
|
||||
ds.deviceType = HARDWARE.get_device_type()
|
||||
ds.started = args.started
|
||||
ds.networkType = network_type
|
||||
ds.networkStrength = network_strength
|
||||
ds.networkMetered = args.metered
|
||||
ds.lastAthenaPingTime = time.monotonic_ns()
|
||||
|
||||
# Keep common sidebar values reasonable for desktop demos.
|
||||
ds.freeSpacePercent = 80
|
||||
ds.memoryUsagePercent = 35
|
||||
ds.maxTempC = 45
|
||||
|
||||
pm.send("deviceState", msg)
|
||||
time.sleep(interval)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -1 +1,9 @@
|
||||
generated/
|
||||
generated/*
|
||||
!generated/car.cpp
|
||||
!generated/car.h
|
||||
!generated/pose.cpp
|
||||
!generated/pose.h
|
||||
!generated/libcar.so
|
||||
!generated/libpose.so
|
||||
!generated/car.os
|
||||
!generated/pose.os
|
||||
|
||||
@@ -0,0 +1,661 @@
|
||||
#include "car.h"
|
||||
|
||||
namespace {
|
||||
#define DIM 9
|
||||
#define EDIM 9
|
||||
#define MEDIM 9
|
||||
typedef void (*Hfun)(double *, double *, double *);
|
||||
|
||||
double mass;
|
||||
|
||||
void set_mass(double x){ mass = x;}
|
||||
|
||||
double rotational_inertia;
|
||||
|
||||
void set_rotational_inertia(double x){ rotational_inertia = x;}
|
||||
|
||||
double center_to_front;
|
||||
|
||||
void set_center_to_front(double x){ center_to_front = x;}
|
||||
|
||||
double center_to_rear;
|
||||
|
||||
void set_center_to_rear(double x){ center_to_rear = x;}
|
||||
|
||||
double stiffness_front;
|
||||
|
||||
void set_stiffness_front(double x){ stiffness_front = x;}
|
||||
|
||||
double stiffness_rear;
|
||||
|
||||
void set_stiffness_rear(double x){ stiffness_rear = x;}
|
||||
const static double MAHA_THRESH_25 = 3.8414588206941227;
|
||||
const static double MAHA_THRESH_24 = 5.991464547107981;
|
||||
const static double MAHA_THRESH_30 = 3.8414588206941227;
|
||||
const static double MAHA_THRESH_26 = 3.8414588206941227;
|
||||
const static double MAHA_THRESH_27 = 3.8414588206941227;
|
||||
const static double MAHA_THRESH_29 = 3.8414588206941227;
|
||||
const static double MAHA_THRESH_28 = 3.8414588206941227;
|
||||
const static double MAHA_THRESH_31 = 3.8414588206941227;
|
||||
|
||||
/******************************************************************************
|
||||
* Code generated with SymPy 1.14.0 *
|
||||
* *
|
||||
* See http://www.sympy.org/ for more information. *
|
||||
* *
|
||||
* This file is part of 'ekf' *
|
||||
******************************************************************************/
|
||||
void err_fun(double *nom_x, double *delta_x, double *out_2689391300508487509) {
|
||||
out_2689391300508487509[0] = delta_x[0] + nom_x[0];
|
||||
out_2689391300508487509[1] = delta_x[1] + nom_x[1];
|
||||
out_2689391300508487509[2] = delta_x[2] + nom_x[2];
|
||||
out_2689391300508487509[3] = delta_x[3] + nom_x[3];
|
||||
out_2689391300508487509[4] = delta_x[4] + nom_x[4];
|
||||
out_2689391300508487509[5] = delta_x[5] + nom_x[5];
|
||||
out_2689391300508487509[6] = delta_x[6] + nom_x[6];
|
||||
out_2689391300508487509[7] = delta_x[7] + nom_x[7];
|
||||
out_2689391300508487509[8] = delta_x[8] + nom_x[8];
|
||||
}
|
||||
void inv_err_fun(double *nom_x, double *true_x, double *out_7177783815062799236) {
|
||||
out_7177783815062799236[0] = -nom_x[0] + true_x[0];
|
||||
out_7177783815062799236[1] = -nom_x[1] + true_x[1];
|
||||
out_7177783815062799236[2] = -nom_x[2] + true_x[2];
|
||||
out_7177783815062799236[3] = -nom_x[3] + true_x[3];
|
||||
out_7177783815062799236[4] = -nom_x[4] + true_x[4];
|
||||
out_7177783815062799236[5] = -nom_x[5] + true_x[5];
|
||||
out_7177783815062799236[6] = -nom_x[6] + true_x[6];
|
||||
out_7177783815062799236[7] = -nom_x[7] + true_x[7];
|
||||
out_7177783815062799236[8] = -nom_x[8] + true_x[8];
|
||||
}
|
||||
void H_mod_fun(double *state, double *out_8221602802744378233) {
|
||||
out_8221602802744378233[0] = 1.0;
|
||||
out_8221602802744378233[1] = 0.0;
|
||||
out_8221602802744378233[2] = 0.0;
|
||||
out_8221602802744378233[3] = 0.0;
|
||||
out_8221602802744378233[4] = 0.0;
|
||||
out_8221602802744378233[5] = 0.0;
|
||||
out_8221602802744378233[6] = 0.0;
|
||||
out_8221602802744378233[7] = 0.0;
|
||||
out_8221602802744378233[8] = 0.0;
|
||||
out_8221602802744378233[9] = 0.0;
|
||||
out_8221602802744378233[10] = 1.0;
|
||||
out_8221602802744378233[11] = 0.0;
|
||||
out_8221602802744378233[12] = 0.0;
|
||||
out_8221602802744378233[13] = 0.0;
|
||||
out_8221602802744378233[14] = 0.0;
|
||||
out_8221602802744378233[15] = 0.0;
|
||||
out_8221602802744378233[16] = 0.0;
|
||||
out_8221602802744378233[17] = 0.0;
|
||||
out_8221602802744378233[18] = 0.0;
|
||||
out_8221602802744378233[19] = 0.0;
|
||||
out_8221602802744378233[20] = 1.0;
|
||||
out_8221602802744378233[21] = 0.0;
|
||||
out_8221602802744378233[22] = 0.0;
|
||||
out_8221602802744378233[23] = 0.0;
|
||||
out_8221602802744378233[24] = 0.0;
|
||||
out_8221602802744378233[25] = 0.0;
|
||||
out_8221602802744378233[26] = 0.0;
|
||||
out_8221602802744378233[27] = 0.0;
|
||||
out_8221602802744378233[28] = 0.0;
|
||||
out_8221602802744378233[29] = 0.0;
|
||||
out_8221602802744378233[30] = 1.0;
|
||||
out_8221602802744378233[31] = 0.0;
|
||||
out_8221602802744378233[32] = 0.0;
|
||||
out_8221602802744378233[33] = 0.0;
|
||||
out_8221602802744378233[34] = 0.0;
|
||||
out_8221602802744378233[35] = 0.0;
|
||||
out_8221602802744378233[36] = 0.0;
|
||||
out_8221602802744378233[37] = 0.0;
|
||||
out_8221602802744378233[38] = 0.0;
|
||||
out_8221602802744378233[39] = 0.0;
|
||||
out_8221602802744378233[40] = 1.0;
|
||||
out_8221602802744378233[41] = 0.0;
|
||||
out_8221602802744378233[42] = 0.0;
|
||||
out_8221602802744378233[43] = 0.0;
|
||||
out_8221602802744378233[44] = 0.0;
|
||||
out_8221602802744378233[45] = 0.0;
|
||||
out_8221602802744378233[46] = 0.0;
|
||||
out_8221602802744378233[47] = 0.0;
|
||||
out_8221602802744378233[48] = 0.0;
|
||||
out_8221602802744378233[49] = 0.0;
|
||||
out_8221602802744378233[50] = 1.0;
|
||||
out_8221602802744378233[51] = 0.0;
|
||||
out_8221602802744378233[52] = 0.0;
|
||||
out_8221602802744378233[53] = 0.0;
|
||||
out_8221602802744378233[54] = 0.0;
|
||||
out_8221602802744378233[55] = 0.0;
|
||||
out_8221602802744378233[56] = 0.0;
|
||||
out_8221602802744378233[57] = 0.0;
|
||||
out_8221602802744378233[58] = 0.0;
|
||||
out_8221602802744378233[59] = 0.0;
|
||||
out_8221602802744378233[60] = 1.0;
|
||||
out_8221602802744378233[61] = 0.0;
|
||||
out_8221602802744378233[62] = 0.0;
|
||||
out_8221602802744378233[63] = 0.0;
|
||||
out_8221602802744378233[64] = 0.0;
|
||||
out_8221602802744378233[65] = 0.0;
|
||||
out_8221602802744378233[66] = 0.0;
|
||||
out_8221602802744378233[67] = 0.0;
|
||||
out_8221602802744378233[68] = 0.0;
|
||||
out_8221602802744378233[69] = 0.0;
|
||||
out_8221602802744378233[70] = 1.0;
|
||||
out_8221602802744378233[71] = 0.0;
|
||||
out_8221602802744378233[72] = 0.0;
|
||||
out_8221602802744378233[73] = 0.0;
|
||||
out_8221602802744378233[74] = 0.0;
|
||||
out_8221602802744378233[75] = 0.0;
|
||||
out_8221602802744378233[76] = 0.0;
|
||||
out_8221602802744378233[77] = 0.0;
|
||||
out_8221602802744378233[78] = 0.0;
|
||||
out_8221602802744378233[79] = 0.0;
|
||||
out_8221602802744378233[80] = 1.0;
|
||||
}
|
||||
void f_fun(double *state, double dt, double *out_7651705913211861388) {
|
||||
out_7651705913211861388[0] = state[0];
|
||||
out_7651705913211861388[1] = state[1];
|
||||
out_7651705913211861388[2] = state[2];
|
||||
out_7651705913211861388[3] = state[3];
|
||||
out_7651705913211861388[4] = state[4];
|
||||
out_7651705913211861388[5] = dt*((-state[4] + (-center_to_front*stiffness_front*state[0] + center_to_rear*stiffness_rear*state[0])/(mass*state[4]))*state[6] - 9.8100000000000005*state[8] + stiffness_front*(-state[2] - state[3] + state[7])*state[0]/(mass*state[1]) + (-stiffness_front*state[0] - stiffness_rear*state[0])*state[5]/(mass*state[4])) + state[5];
|
||||
out_7651705913211861388[6] = dt*(center_to_front*stiffness_front*(-state[2] - state[3] + state[7])*state[0]/(rotational_inertia*state[1]) + (-center_to_front*stiffness_front*state[0] + center_to_rear*stiffness_rear*state[0])*state[5]/(rotational_inertia*state[4]) + (-pow(center_to_front, 2)*stiffness_front*state[0] - pow(center_to_rear, 2)*stiffness_rear*state[0])*state[6]/(rotational_inertia*state[4])) + state[6];
|
||||
out_7651705913211861388[7] = state[7];
|
||||
out_7651705913211861388[8] = state[8];
|
||||
}
|
||||
void F_fun(double *state, double dt, double *out_97859790539154602) {
|
||||
out_97859790539154602[0] = 1;
|
||||
out_97859790539154602[1] = 0;
|
||||
out_97859790539154602[2] = 0;
|
||||
out_97859790539154602[3] = 0;
|
||||
out_97859790539154602[4] = 0;
|
||||
out_97859790539154602[5] = 0;
|
||||
out_97859790539154602[6] = 0;
|
||||
out_97859790539154602[7] = 0;
|
||||
out_97859790539154602[8] = 0;
|
||||
out_97859790539154602[9] = 0;
|
||||
out_97859790539154602[10] = 1;
|
||||
out_97859790539154602[11] = 0;
|
||||
out_97859790539154602[12] = 0;
|
||||
out_97859790539154602[13] = 0;
|
||||
out_97859790539154602[14] = 0;
|
||||
out_97859790539154602[15] = 0;
|
||||
out_97859790539154602[16] = 0;
|
||||
out_97859790539154602[17] = 0;
|
||||
out_97859790539154602[18] = 0;
|
||||
out_97859790539154602[19] = 0;
|
||||
out_97859790539154602[20] = 1;
|
||||
out_97859790539154602[21] = 0;
|
||||
out_97859790539154602[22] = 0;
|
||||
out_97859790539154602[23] = 0;
|
||||
out_97859790539154602[24] = 0;
|
||||
out_97859790539154602[25] = 0;
|
||||
out_97859790539154602[26] = 0;
|
||||
out_97859790539154602[27] = 0;
|
||||
out_97859790539154602[28] = 0;
|
||||
out_97859790539154602[29] = 0;
|
||||
out_97859790539154602[30] = 1;
|
||||
out_97859790539154602[31] = 0;
|
||||
out_97859790539154602[32] = 0;
|
||||
out_97859790539154602[33] = 0;
|
||||
out_97859790539154602[34] = 0;
|
||||
out_97859790539154602[35] = 0;
|
||||
out_97859790539154602[36] = 0;
|
||||
out_97859790539154602[37] = 0;
|
||||
out_97859790539154602[38] = 0;
|
||||
out_97859790539154602[39] = 0;
|
||||
out_97859790539154602[40] = 1;
|
||||
out_97859790539154602[41] = 0;
|
||||
out_97859790539154602[42] = 0;
|
||||
out_97859790539154602[43] = 0;
|
||||
out_97859790539154602[44] = 0;
|
||||
out_97859790539154602[45] = dt*(stiffness_front*(-state[2] - state[3] + state[7])/(mass*state[1]) + (-stiffness_front - stiffness_rear)*state[5]/(mass*state[4]) + (-center_to_front*stiffness_front + center_to_rear*stiffness_rear)*state[6]/(mass*state[4]));
|
||||
out_97859790539154602[46] = -dt*stiffness_front*(-state[2] - state[3] + state[7])*state[0]/(mass*pow(state[1], 2));
|
||||
out_97859790539154602[47] = -dt*stiffness_front*state[0]/(mass*state[1]);
|
||||
out_97859790539154602[48] = -dt*stiffness_front*state[0]/(mass*state[1]);
|
||||
out_97859790539154602[49] = dt*((-1 - (-center_to_front*stiffness_front*state[0] + center_to_rear*stiffness_rear*state[0])/(mass*pow(state[4], 2)))*state[6] - (-stiffness_front*state[0] - stiffness_rear*state[0])*state[5]/(mass*pow(state[4], 2)));
|
||||
out_97859790539154602[50] = dt*(-stiffness_front*state[0] - stiffness_rear*state[0])/(mass*state[4]) + 1;
|
||||
out_97859790539154602[51] = dt*(-state[4] + (-center_to_front*stiffness_front*state[0] + center_to_rear*stiffness_rear*state[0])/(mass*state[4]));
|
||||
out_97859790539154602[52] = dt*stiffness_front*state[0]/(mass*state[1]);
|
||||
out_97859790539154602[53] = -9.8100000000000005*dt;
|
||||
out_97859790539154602[54] = dt*(center_to_front*stiffness_front*(-state[2] - state[3] + state[7])/(rotational_inertia*state[1]) + (-center_to_front*stiffness_front + center_to_rear*stiffness_rear)*state[5]/(rotational_inertia*state[4]) + (-pow(center_to_front, 2)*stiffness_front - pow(center_to_rear, 2)*stiffness_rear)*state[6]/(rotational_inertia*state[4]));
|
||||
out_97859790539154602[55] = -center_to_front*dt*stiffness_front*(-state[2] - state[3] + state[7])*state[0]/(rotational_inertia*pow(state[1], 2));
|
||||
out_97859790539154602[56] = -center_to_front*dt*stiffness_front*state[0]/(rotational_inertia*state[1]);
|
||||
out_97859790539154602[57] = -center_to_front*dt*stiffness_front*state[0]/(rotational_inertia*state[1]);
|
||||
out_97859790539154602[58] = dt*(-(-center_to_front*stiffness_front*state[0] + center_to_rear*stiffness_rear*state[0])*state[5]/(rotational_inertia*pow(state[4], 2)) - (-pow(center_to_front, 2)*stiffness_front*state[0] - pow(center_to_rear, 2)*stiffness_rear*state[0])*state[6]/(rotational_inertia*pow(state[4], 2)));
|
||||
out_97859790539154602[59] = dt*(-center_to_front*stiffness_front*state[0] + center_to_rear*stiffness_rear*state[0])/(rotational_inertia*state[4]);
|
||||
out_97859790539154602[60] = dt*(-pow(center_to_front, 2)*stiffness_front*state[0] - pow(center_to_rear, 2)*stiffness_rear*state[0])/(rotational_inertia*state[4]) + 1;
|
||||
out_97859790539154602[61] = center_to_front*dt*stiffness_front*state[0]/(rotational_inertia*state[1]);
|
||||
out_97859790539154602[62] = 0;
|
||||
out_97859790539154602[63] = 0;
|
||||
out_97859790539154602[64] = 0;
|
||||
out_97859790539154602[65] = 0;
|
||||
out_97859790539154602[66] = 0;
|
||||
out_97859790539154602[67] = 0;
|
||||
out_97859790539154602[68] = 0;
|
||||
out_97859790539154602[69] = 0;
|
||||
out_97859790539154602[70] = 1;
|
||||
out_97859790539154602[71] = 0;
|
||||
out_97859790539154602[72] = 0;
|
||||
out_97859790539154602[73] = 0;
|
||||
out_97859790539154602[74] = 0;
|
||||
out_97859790539154602[75] = 0;
|
||||
out_97859790539154602[76] = 0;
|
||||
out_97859790539154602[77] = 0;
|
||||
out_97859790539154602[78] = 0;
|
||||
out_97859790539154602[79] = 0;
|
||||
out_97859790539154602[80] = 1;
|
||||
}
|
||||
void h_25(double *state, double *unused, double *out_1747255377487496462) {
|
||||
out_1747255377487496462[0] = state[6];
|
||||
}
|
||||
void H_25(double *state, double *unused, double *out_7588584345949747189) {
|
||||
out_7588584345949747189[0] = 0;
|
||||
out_7588584345949747189[1] = 0;
|
||||
out_7588584345949747189[2] = 0;
|
||||
out_7588584345949747189[3] = 0;
|
||||
out_7588584345949747189[4] = 0;
|
||||
out_7588584345949747189[5] = 0;
|
||||
out_7588584345949747189[6] = 1;
|
||||
out_7588584345949747189[7] = 0;
|
||||
out_7588584345949747189[8] = 0;
|
||||
}
|
||||
void h_24(double *state, double *unused, double *out_3070396560078381804) {
|
||||
out_3070396560078381804[0] = state[4];
|
||||
out_3070396560078381804[1] = state[5];
|
||||
}
|
||||
void H_24(double *state, double *unused, double *out_7300234128957481291) {
|
||||
out_7300234128957481291[0] = 0;
|
||||
out_7300234128957481291[1] = 0;
|
||||
out_7300234128957481291[2] = 0;
|
||||
out_7300234128957481291[3] = 0;
|
||||
out_7300234128957481291[4] = 1;
|
||||
out_7300234128957481291[5] = 0;
|
||||
out_7300234128957481291[6] = 0;
|
||||
out_7300234128957481291[7] = 0;
|
||||
out_7300234128957481291[8] = 0;
|
||||
out_7300234128957481291[9] = 0;
|
||||
out_7300234128957481291[10] = 0;
|
||||
out_7300234128957481291[11] = 0;
|
||||
out_7300234128957481291[12] = 0;
|
||||
out_7300234128957481291[13] = 0;
|
||||
out_7300234128957481291[14] = 1;
|
||||
out_7300234128957481291[15] = 0;
|
||||
out_7300234128957481291[16] = 0;
|
||||
out_7300234128957481291[17] = 0;
|
||||
}
|
||||
void h_30(double *state, double *unused, double *out_2594165583737162996) {
|
||||
out_2594165583737162996[0] = state[4];
|
||||
}
|
||||
void H_30(double *state, double *unused, double *out_8339826769252555800) {
|
||||
out_8339826769252555800[0] = 0;
|
||||
out_8339826769252555800[1] = 0;
|
||||
out_8339826769252555800[2] = 0;
|
||||
out_8339826769252555800[3] = 0;
|
||||
out_8339826769252555800[4] = 1;
|
||||
out_8339826769252555800[5] = 0;
|
||||
out_8339826769252555800[6] = 0;
|
||||
out_8339826769252555800[7] = 0;
|
||||
out_8339826769252555800[8] = 0;
|
||||
}
|
||||
void h_26(double *state, double *unused, double *out_1234538052727793168) {
|
||||
out_1234538052727793168[0] = state[7];
|
||||
}
|
||||
void H_26(double *state, double *unused, double *out_3847081027075690965) {
|
||||
out_3847081027075690965[0] = 0;
|
||||
out_3847081027075690965[1] = 0;
|
||||
out_3847081027075690965[2] = 0;
|
||||
out_3847081027075690965[3] = 0;
|
||||
out_3847081027075690965[4] = 0;
|
||||
out_3847081027075690965[5] = 0;
|
||||
out_3847081027075690965[6] = 0;
|
||||
out_3847081027075690965[7] = 1;
|
||||
out_3847081027075690965[8] = 0;
|
||||
}
|
||||
void h_27(double *state, double *unused, double *out_4784041428931829147) {
|
||||
out_4784041428931829147[0] = state[3];
|
||||
}
|
||||
void H_27(double *state, double *unused, double *out_886124704021714080) {
|
||||
out_886124704021714080[0] = 0;
|
||||
out_886124704021714080[1] = 0;
|
||||
out_886124704021714080[2] = 0;
|
||||
out_886124704021714080[3] = 1;
|
||||
out_886124704021714080[4] = 0;
|
||||
out_886124704021714080[5] = 0;
|
||||
out_886124704021714080[6] = 0;
|
||||
out_886124704021714080[7] = 0;
|
||||
out_886124704021714080[8] = 0;
|
||||
}
|
||||
void h_29(double *state, double *unused, double *out_2407507683923682649) {
|
||||
out_2407507683923682649[0] = state[1];
|
||||
}
|
||||
void H_29(double *state, double *unused, double *out_3571119360136531175) {
|
||||
out_3571119360136531175[0] = 0;
|
||||
out_3571119360136531175[1] = 1;
|
||||
out_3571119360136531175[2] = 0;
|
||||
out_3571119360136531175[3] = 0;
|
||||
out_3571119360136531175[4] = 0;
|
||||
out_3571119360136531175[5] = 0;
|
||||
out_3571119360136531175[6] = 0;
|
||||
out_3571119360136531175[7] = 0;
|
||||
out_3571119360136531175[8] = 0;
|
||||
}
|
||||
void h_28(double *state, double *unused, double *out_7679778805471580716) {
|
||||
out_7679778805471580716[0] = state[0];
|
||||
}
|
||||
void H_28(double *state, double *unused, double *out_5534749631701857426) {
|
||||
out_5534749631701857426[0] = 1;
|
||||
out_5534749631701857426[1] = 0;
|
||||
out_5534749631701857426[2] = 0;
|
||||
out_5534749631701857426[3] = 0;
|
||||
out_5534749631701857426[4] = 0;
|
||||
out_5534749631701857426[5] = 0;
|
||||
out_5534749631701857426[6] = 0;
|
||||
out_5534749631701857426[7] = 0;
|
||||
out_5534749631701857426[8] = 0;
|
||||
}
|
||||
void h_31(double *state, double *unused, double *out_5023579848862854474) {
|
||||
out_5023579848862854474[0] = state[8];
|
||||
}
|
||||
void H_31(double *state, double *unused, double *out_3220872924842339489) {
|
||||
out_3220872924842339489[0] = 0;
|
||||
out_3220872924842339489[1] = 0;
|
||||
out_3220872924842339489[2] = 0;
|
||||
out_3220872924842339489[3] = 0;
|
||||
out_3220872924842339489[4] = 0;
|
||||
out_3220872924842339489[5] = 0;
|
||||
out_3220872924842339489[6] = 0;
|
||||
out_3220872924842339489[7] = 0;
|
||||
out_3220872924842339489[8] = 1;
|
||||
}
|
||||
#include <eigen3/Eigen/Dense>
|
||||
#include <iostream>
|
||||
|
||||
typedef Eigen::Matrix<double, DIM, DIM, Eigen::RowMajor> DDM;
|
||||
typedef Eigen::Matrix<double, EDIM, EDIM, Eigen::RowMajor> EEM;
|
||||
typedef Eigen::Matrix<double, DIM, EDIM, Eigen::RowMajor> DEM;
|
||||
|
||||
void predict(double *in_x, double *in_P, double *in_Q, double dt) {
|
||||
typedef Eigen::Matrix<double, MEDIM, MEDIM, Eigen::RowMajor> RRM;
|
||||
|
||||
double nx[DIM] = {0};
|
||||
double in_F[EDIM*EDIM] = {0};
|
||||
|
||||
// functions from sympy
|
||||
f_fun(in_x, dt, nx);
|
||||
F_fun(in_x, dt, in_F);
|
||||
|
||||
|
||||
EEM F(in_F);
|
||||
EEM P(in_P);
|
||||
EEM Q(in_Q);
|
||||
|
||||
RRM F_main = F.topLeftCorner(MEDIM, MEDIM);
|
||||
P.topLeftCorner(MEDIM, MEDIM) = (F_main * P.topLeftCorner(MEDIM, MEDIM)) * F_main.transpose();
|
||||
P.topRightCorner(MEDIM, EDIM - MEDIM) = F_main * P.topRightCorner(MEDIM, EDIM - MEDIM);
|
||||
P.bottomLeftCorner(EDIM - MEDIM, MEDIM) = P.bottomLeftCorner(EDIM - MEDIM, MEDIM) * F_main.transpose();
|
||||
|
||||
P = P + dt*Q;
|
||||
|
||||
// copy out state
|
||||
memcpy(in_x, nx, DIM * sizeof(double));
|
||||
memcpy(in_P, P.data(), EDIM * EDIM * sizeof(double));
|
||||
}
|
||||
|
||||
// note: extra_args dim only correct when null space projecting
|
||||
// otherwise 1
|
||||
template <int ZDIM, int EADIM, bool MAHA_TEST>
|
||||
void update(double *in_x, double *in_P, Hfun h_fun, Hfun H_fun, Hfun Hea_fun, double *in_z, double *in_R, double *in_ea, double MAHA_THRESHOLD) {
|
||||
typedef Eigen::Matrix<double, ZDIM, ZDIM, Eigen::RowMajor> ZZM;
|
||||
typedef Eigen::Matrix<double, ZDIM, DIM, Eigen::RowMajor> ZDM;
|
||||
typedef Eigen::Matrix<double, Eigen::Dynamic, EDIM, Eigen::RowMajor> XEM;
|
||||
//typedef Eigen::Matrix<double, EDIM, ZDIM, Eigen::RowMajor> EZM;
|
||||
typedef Eigen::Matrix<double, Eigen::Dynamic, 1> X1M;
|
||||
typedef Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> XXM;
|
||||
|
||||
double in_hx[ZDIM] = {0};
|
||||
double in_H[ZDIM * DIM] = {0};
|
||||
double in_H_mod[EDIM * DIM] = {0};
|
||||
double delta_x[EDIM] = {0};
|
||||
double x_new[DIM] = {0};
|
||||
|
||||
|
||||
// state x, P
|
||||
Eigen::Matrix<double, ZDIM, 1> z(in_z);
|
||||
EEM P(in_P);
|
||||
ZZM pre_R(in_R);
|
||||
|
||||
// functions from sympy
|
||||
h_fun(in_x, in_ea, in_hx);
|
||||
H_fun(in_x, in_ea, in_H);
|
||||
ZDM pre_H(in_H);
|
||||
|
||||
// get y (y = z - hx)
|
||||
Eigen::Matrix<double, ZDIM, 1> pre_y(in_hx); pre_y = z - pre_y;
|
||||
X1M y; XXM H; XXM R;
|
||||
if (Hea_fun){
|
||||
typedef Eigen::Matrix<double, ZDIM, EADIM, Eigen::RowMajor> ZAM;
|
||||
double in_Hea[ZDIM * EADIM] = {0};
|
||||
Hea_fun(in_x, in_ea, in_Hea);
|
||||
ZAM Hea(in_Hea);
|
||||
XXM A = Hea.transpose().fullPivLu().kernel();
|
||||
|
||||
|
||||
y = A.transpose() * pre_y;
|
||||
H = A.transpose() * pre_H;
|
||||
R = A.transpose() * pre_R * A;
|
||||
} else {
|
||||
y = pre_y;
|
||||
H = pre_H;
|
||||
R = pre_R;
|
||||
}
|
||||
// get modified H
|
||||
H_mod_fun(in_x, in_H_mod);
|
||||
DEM H_mod(in_H_mod);
|
||||
XEM H_err = H * H_mod;
|
||||
|
||||
// Do mahalobis distance test
|
||||
if (MAHA_TEST){
|
||||
XXM a = (H_err * P * H_err.transpose() + R).inverse();
|
||||
double maha_dist = y.transpose() * a * y;
|
||||
if (maha_dist > MAHA_THRESHOLD){
|
||||
R = 1.0e16 * R;
|
||||
}
|
||||
}
|
||||
|
||||
// Outlier resilient weighting
|
||||
double weight = 1;//(1.5)/(1 + y.squaredNorm()/R.sum());
|
||||
|
||||
// kalman gains and I_KH
|
||||
XXM S = ((H_err * P) * H_err.transpose()) + R/weight;
|
||||
XEM KT = S.fullPivLu().solve(H_err * P.transpose());
|
||||
//EZM K = KT.transpose(); TODO: WHY DOES THIS NOT COMPILE?
|
||||
//EZM K = S.fullPivLu().solve(H_err * P.transpose()).transpose();
|
||||
//std::cout << "Here is the matrix rot:\n" << K << std::endl;
|
||||
EEM I_KH = Eigen::Matrix<double, EDIM, EDIM>::Identity() - (KT.transpose() * H_err);
|
||||
|
||||
// update state by injecting dx
|
||||
Eigen::Matrix<double, EDIM, 1> dx(delta_x);
|
||||
dx = (KT.transpose() * y);
|
||||
memcpy(delta_x, dx.data(), EDIM * sizeof(double));
|
||||
err_fun(in_x, delta_x, x_new);
|
||||
Eigen::Matrix<double, DIM, 1> x(x_new);
|
||||
|
||||
// update cov
|
||||
P = ((I_KH * P) * I_KH.transpose()) + ((KT.transpose() * R) * KT);
|
||||
|
||||
// copy out state
|
||||
memcpy(in_x, x.data(), DIM * sizeof(double));
|
||||
memcpy(in_P, P.data(), EDIM * EDIM * sizeof(double));
|
||||
memcpy(in_z, y.data(), y.rows() * sizeof(double));
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
}
|
||||
extern "C" {
|
||||
|
||||
void car_update_25(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea) {
|
||||
update<1, 3, 0>(in_x, in_P, h_25, H_25, NULL, in_z, in_R, in_ea, MAHA_THRESH_25);
|
||||
}
|
||||
void car_update_24(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea) {
|
||||
update<2, 3, 0>(in_x, in_P, h_24, H_24, NULL, in_z, in_R, in_ea, MAHA_THRESH_24);
|
||||
}
|
||||
void car_update_30(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea) {
|
||||
update<1, 3, 0>(in_x, in_P, h_30, H_30, NULL, in_z, in_R, in_ea, MAHA_THRESH_30);
|
||||
}
|
||||
void car_update_26(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea) {
|
||||
update<1, 3, 0>(in_x, in_P, h_26, H_26, NULL, in_z, in_R, in_ea, MAHA_THRESH_26);
|
||||
}
|
||||
void car_update_27(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea) {
|
||||
update<1, 3, 0>(in_x, in_P, h_27, H_27, NULL, in_z, in_R, in_ea, MAHA_THRESH_27);
|
||||
}
|
||||
void car_update_29(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea) {
|
||||
update<1, 3, 0>(in_x, in_P, h_29, H_29, NULL, in_z, in_R, in_ea, MAHA_THRESH_29);
|
||||
}
|
||||
void car_update_28(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea) {
|
||||
update<1, 3, 0>(in_x, in_P, h_28, H_28, NULL, in_z, in_R, in_ea, MAHA_THRESH_28);
|
||||
}
|
||||
void car_update_31(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea) {
|
||||
update<1, 3, 0>(in_x, in_P, h_31, H_31, NULL, in_z, in_R, in_ea, MAHA_THRESH_31);
|
||||
}
|
||||
void car_err_fun(double *nom_x, double *delta_x, double *out_2689391300508487509) {
|
||||
err_fun(nom_x, delta_x, out_2689391300508487509);
|
||||
}
|
||||
void car_inv_err_fun(double *nom_x, double *true_x, double *out_7177783815062799236) {
|
||||
inv_err_fun(nom_x, true_x, out_7177783815062799236);
|
||||
}
|
||||
void car_H_mod_fun(double *state, double *out_8221602802744378233) {
|
||||
H_mod_fun(state, out_8221602802744378233);
|
||||
}
|
||||
void car_f_fun(double *state, double dt, double *out_7651705913211861388) {
|
||||
f_fun(state, dt, out_7651705913211861388);
|
||||
}
|
||||
void car_F_fun(double *state, double dt, double *out_97859790539154602) {
|
||||
F_fun(state, dt, out_97859790539154602);
|
||||
}
|
||||
void car_h_25(double *state, double *unused, double *out_1747255377487496462) {
|
||||
h_25(state, unused, out_1747255377487496462);
|
||||
}
|
||||
void car_H_25(double *state, double *unused, double *out_7588584345949747189) {
|
||||
H_25(state, unused, out_7588584345949747189);
|
||||
}
|
||||
void car_h_24(double *state, double *unused, double *out_3070396560078381804) {
|
||||
h_24(state, unused, out_3070396560078381804);
|
||||
}
|
||||
void car_H_24(double *state, double *unused, double *out_7300234128957481291) {
|
||||
H_24(state, unused, out_7300234128957481291);
|
||||
}
|
||||
void car_h_30(double *state, double *unused, double *out_2594165583737162996) {
|
||||
h_30(state, unused, out_2594165583737162996);
|
||||
}
|
||||
void car_H_30(double *state, double *unused, double *out_8339826769252555800) {
|
||||
H_30(state, unused, out_8339826769252555800);
|
||||
}
|
||||
void car_h_26(double *state, double *unused, double *out_1234538052727793168) {
|
||||
h_26(state, unused, out_1234538052727793168);
|
||||
}
|
||||
void car_H_26(double *state, double *unused, double *out_3847081027075690965) {
|
||||
H_26(state, unused, out_3847081027075690965);
|
||||
}
|
||||
void car_h_27(double *state, double *unused, double *out_4784041428931829147) {
|
||||
h_27(state, unused, out_4784041428931829147);
|
||||
}
|
||||
void car_H_27(double *state, double *unused, double *out_886124704021714080) {
|
||||
H_27(state, unused, out_886124704021714080);
|
||||
}
|
||||
void car_h_29(double *state, double *unused, double *out_2407507683923682649) {
|
||||
h_29(state, unused, out_2407507683923682649);
|
||||
}
|
||||
void car_H_29(double *state, double *unused, double *out_3571119360136531175) {
|
||||
H_29(state, unused, out_3571119360136531175);
|
||||
}
|
||||
void car_h_28(double *state, double *unused, double *out_7679778805471580716) {
|
||||
h_28(state, unused, out_7679778805471580716);
|
||||
}
|
||||
void car_H_28(double *state, double *unused, double *out_5534749631701857426) {
|
||||
H_28(state, unused, out_5534749631701857426);
|
||||
}
|
||||
void car_h_31(double *state, double *unused, double *out_5023579848862854474) {
|
||||
h_31(state, unused, out_5023579848862854474);
|
||||
}
|
||||
void car_H_31(double *state, double *unused, double *out_3220872924842339489) {
|
||||
H_31(state, unused, out_3220872924842339489);
|
||||
}
|
||||
void car_predict(double *in_x, double *in_P, double *in_Q, double dt) {
|
||||
predict(in_x, in_P, in_Q, dt);
|
||||
}
|
||||
void car_set_mass(double x) {
|
||||
set_mass(x);
|
||||
}
|
||||
void car_set_rotational_inertia(double x) {
|
||||
set_rotational_inertia(x);
|
||||
}
|
||||
void car_set_center_to_front(double x) {
|
||||
set_center_to_front(x);
|
||||
}
|
||||
void car_set_center_to_rear(double x) {
|
||||
set_center_to_rear(x);
|
||||
}
|
||||
void car_set_stiffness_front(double x) {
|
||||
set_stiffness_front(x);
|
||||
}
|
||||
void car_set_stiffness_rear(double x) {
|
||||
set_stiffness_rear(x);
|
||||
}
|
||||
}
|
||||
|
||||
const EKF car = {
|
||||
.name = "car",
|
||||
.kinds = { 25, 24, 30, 26, 27, 29, 28, 31 },
|
||||
.feature_kinds = { },
|
||||
.f_fun = car_f_fun,
|
||||
.F_fun = car_F_fun,
|
||||
.err_fun = car_err_fun,
|
||||
.inv_err_fun = car_inv_err_fun,
|
||||
.H_mod_fun = car_H_mod_fun,
|
||||
.predict = car_predict,
|
||||
.hs = {
|
||||
{ 25, car_h_25 },
|
||||
{ 24, car_h_24 },
|
||||
{ 30, car_h_30 },
|
||||
{ 26, car_h_26 },
|
||||
{ 27, car_h_27 },
|
||||
{ 29, car_h_29 },
|
||||
{ 28, car_h_28 },
|
||||
{ 31, car_h_31 },
|
||||
},
|
||||
.Hs = {
|
||||
{ 25, car_H_25 },
|
||||
{ 24, car_H_24 },
|
||||
{ 30, car_H_30 },
|
||||
{ 26, car_H_26 },
|
||||
{ 27, car_H_27 },
|
||||
{ 29, car_H_29 },
|
||||
{ 28, car_H_28 },
|
||||
{ 31, car_H_31 },
|
||||
},
|
||||
.updates = {
|
||||
{ 25, car_update_25 },
|
||||
{ 24, car_update_24 },
|
||||
{ 30, car_update_30 },
|
||||
{ 26, car_update_26 },
|
||||
{ 27, car_update_27 },
|
||||
{ 29, car_update_29 },
|
||||
{ 28, car_update_28 },
|
||||
{ 31, car_update_31 },
|
||||
},
|
||||
.Hes = {
|
||||
},
|
||||
.sets = {
|
||||
{ "mass", car_set_mass },
|
||||
{ "rotational_inertia", car_set_rotational_inertia },
|
||||
{ "center_to_front", car_set_center_to_front },
|
||||
{ "center_to_rear", car_set_center_to_rear },
|
||||
{ "stiffness_front", car_set_stiffness_front },
|
||||
{ "stiffness_rear", car_set_stiffness_rear },
|
||||
},
|
||||
.extra_routines = {
|
||||
},
|
||||
};
|
||||
|
||||
ekf_lib_init(car)
|
||||
@@ -0,0 +1,40 @@
|
||||
#pragma once
|
||||
#include "rednose/helpers/ekf.h"
|
||||
extern "C" {
|
||||
void car_update_25(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea);
|
||||
void car_update_24(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea);
|
||||
void car_update_30(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea);
|
||||
void car_update_26(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea);
|
||||
void car_update_27(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea);
|
||||
void car_update_29(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea);
|
||||
void car_update_28(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea);
|
||||
void car_update_31(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea);
|
||||
void car_err_fun(double *nom_x, double *delta_x, double *out_2689391300508487509);
|
||||
void car_inv_err_fun(double *nom_x, double *true_x, double *out_7177783815062799236);
|
||||
void car_H_mod_fun(double *state, double *out_8221602802744378233);
|
||||
void car_f_fun(double *state, double dt, double *out_7651705913211861388);
|
||||
void car_F_fun(double *state, double dt, double *out_97859790539154602);
|
||||
void car_h_25(double *state, double *unused, double *out_1747255377487496462);
|
||||
void car_H_25(double *state, double *unused, double *out_7588584345949747189);
|
||||
void car_h_24(double *state, double *unused, double *out_3070396560078381804);
|
||||
void car_H_24(double *state, double *unused, double *out_7300234128957481291);
|
||||
void car_h_30(double *state, double *unused, double *out_2594165583737162996);
|
||||
void car_H_30(double *state, double *unused, double *out_8339826769252555800);
|
||||
void car_h_26(double *state, double *unused, double *out_1234538052727793168);
|
||||
void car_H_26(double *state, double *unused, double *out_3847081027075690965);
|
||||
void car_h_27(double *state, double *unused, double *out_4784041428931829147);
|
||||
void car_H_27(double *state, double *unused, double *out_886124704021714080);
|
||||
void car_h_29(double *state, double *unused, double *out_2407507683923682649);
|
||||
void car_H_29(double *state, double *unused, double *out_3571119360136531175);
|
||||
void car_h_28(double *state, double *unused, double *out_7679778805471580716);
|
||||
void car_H_28(double *state, double *unused, double *out_5534749631701857426);
|
||||
void car_h_31(double *state, double *unused, double *out_5023579848862854474);
|
||||
void car_H_31(double *state, double *unused, double *out_3220872924842339489);
|
||||
void car_predict(double *in_x, double *in_P, double *in_Q, double dt);
|
||||
void car_set_mass(double x);
|
||||
void car_set_rotational_inertia(double x);
|
||||
void car_set_center_to_front(double x);
|
||||
void car_set_center_to_rear(double x);
|
||||
void car_set_stiffness_front(double x);
|
||||
void car_set_stiffness_rear(double x);
|
||||
}
|
||||
Binary file not shown.
BIN
Binary file not shown.
BIN
Binary file not shown.
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,22 @@
|
||||
#pragma once
|
||||
#include "rednose/helpers/ekf.h"
|
||||
extern "C" {
|
||||
void pose_update_4(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea);
|
||||
void pose_update_10(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea);
|
||||
void pose_update_13(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea);
|
||||
void pose_update_14(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea);
|
||||
void pose_err_fun(double *nom_x, double *delta_x, double *out_2843212773844661672);
|
||||
void pose_inv_err_fun(double *nom_x, double *true_x, double *out_2943105406875713938);
|
||||
void pose_H_mod_fun(double *state, double *out_2147512711416992695);
|
||||
void pose_f_fun(double *state, double dt, double *out_9076294150866414245);
|
||||
void pose_F_fun(double *state, double dt, double *out_4995496673877862289);
|
||||
void pose_h_4(double *state, double *unused, double *out_7356118181286553510);
|
||||
void pose_H_4(double *state, double *unused, double *out_3967211437323289556);
|
||||
void pose_h_10(double *state, double *unused, double *out_320685202434969677);
|
||||
void pose_H_10(double *state, double *unused, double *out_156638784834038850);
|
||||
void pose_h_13(double *state, double *unused, double *out_4281107234856404284);
|
||||
void pose_H_13(double *state, double *unused, double *out_7800966900625813580);
|
||||
void pose_h_14(double *state, double *unused, double *out_3917712072833752253);
|
||||
void pose_H_14(double *state, double *unused, double *out_7049999869618661852);
|
||||
void pose_predict(double *in_x, double *in_P, double *in_Q, double dt);
|
||||
}
|
||||
Binary file not shown.
@@ -1,6 +1,7 @@
|
||||
#!/usr/bin/env python3
|
||||
|
||||
import sys
|
||||
import os
|
||||
import numpy as np
|
||||
|
||||
from openpilot.selfdrive.locationd.models.constants import ObservationKind
|
||||
@@ -102,7 +103,13 @@ class PoseKalman(KalmanFilter):
|
||||
|
||||
def __init__(self, generated_dir, max_rewind_age):
|
||||
dim_state, dim_state_err = PoseKalman.initial_x.shape[0], PoseKalman.initial_P.shape[0]
|
||||
self.filter = EKF_sym_pyx(generated_dir, self.name, PoseKalman.Q, PoseKalman.initial_x, PoseKalman.initial_P,
|
||||
ekf_name = self.name
|
||||
# Compatibility fallback for installs that still carry the older `live` EKF artifacts.
|
||||
if not os.path.exists(os.path.join(generated_dir, f"lib{ekf_name}.so")):
|
||||
live_fallback = os.path.join(generated_dir, "liblive.so")
|
||||
if os.path.exists(live_fallback):
|
||||
ekf_name = "live"
|
||||
self.filter = EKF_sym_pyx(generated_dir, ekf_name, PoseKalman.Q, PoseKalman.initial_x, PoseKalman.initial_P,
|
||||
dim_state, dim_state_err, max_rewind_age=max_rewind_age)
|
||||
|
||||
|
||||
|
||||
+82
-17
@@ -20,39 +20,104 @@ if arch == "Darwin":
|
||||
else:
|
||||
libs += ['OpenCL']
|
||||
|
||||
# Set path definitions
|
||||
for pathdef, fn in {'TRANSFORM': 'transforms/transform.cl', 'LOADYUV': 'transforms/loadyuv.cl'}.items():
|
||||
# Set path definitions to repository-relative paths so prebuilt artifacts stay relocatable.
|
||||
for pathdef, fn in {'TRANSFORM': 'selfdrive/modeld/transforms/transform.cl', 'LOADYUV': 'selfdrive/modeld/transforms/loadyuv.cl'}.items():
|
||||
for xenv in (lenv, lenvCython):
|
||||
xenv['CXXFLAGS'].append(f'-D{pathdef}_PATH=\\"{File(fn).abspath}\\"')
|
||||
xenv['CXXFLAGS'].append(f'-D{pathdef}_PATH=\\"{fn}\\"')
|
||||
|
||||
# Compile cython
|
||||
cython_libs = envCython["LIBS"] + libs
|
||||
commonmodel_lib = lenv.Library('commonmodel', common_src)
|
||||
lenvCython.Program('models/commonmodel_pyx.so', 'models/commonmodel_pyx.pyx', LIBS=[commonmodel_lib, *cython_libs], FRAMEWORKS=frameworks)
|
||||
tinygrad_files = ["#"+x for x in glob.glob(env.Dir("#tinygrad_repo").relpath + "/**", recursive=True, root_dir=env.Dir("#").abspath) if 'pycache' not in x]
|
||||
skip_dm_tinygrad_pkl = os.getenv("SP_SKIP_DM_TINYGRAD_PKL", "").lower() in {"1", "true", "yes", "on"}
|
||||
allow_host_tinygrad_pkl = os.getenv("SP_ALLOW_HOST_TINYGRAD_PKL", "").lower() in {"1", "true", "yes", "on"}
|
||||
build_model_tinygrad_pkl = os.getenv("SP_BUILD_MODEL_TINYGRAD_PKL", "").lower() in {"1", "true", "yes", "on"}
|
||||
has_qcom_gpu = os.path.exists('/dev/kgsl-3d0')
|
||||
|
||||
# Compile camera warp artifacts used by modeld/dmonitoringmodeld on C4.
|
||||
if arch == 'larch64':
|
||||
compile_warp_flags = 'DEV=QCOM FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0' \
|
||||
if os.path.exists('/dev/kgsl-3d0') else 'DEV=CPU CPU=1 THREADS=0 NOLOCALS=1 DEBUG=0 HOME=/tmp'
|
||||
else:
|
||||
compile_warp_flags = {
|
||||
'Darwin': f'DEV=CPU THREADS=0 NOLOCALS=1 DEBUG=0 HOME={os.path.expanduser("~")}',
|
||||
}.get(arch, 'DEV=CPU CPU_LLVM=1 THREADS=0 NOLOCALS=1 DEBUG=0')
|
||||
|
||||
build_warp_artifacts = os.getenv("SP_BUILD_WARP_ARTIFACTS", "").lower() in {"1", "true", "yes", "on"}
|
||||
if build_warp_artifacts:
|
||||
default_warp_resolutions = [(1928, 1208), (1344, 760)]
|
||||
raw_warp_resolutions = os.getenv("SP_WARP_RESOLUTIONS", "").strip()
|
||||
if raw_warp_resolutions:
|
||||
selected_warp_resolutions = []
|
||||
seen_warp_resolutions = set()
|
||||
for token in raw_warp_resolutions.replace(";", ",").split(","):
|
||||
token = token.strip().lower()
|
||||
if not token:
|
||||
continue
|
||||
w_str, h_str = token.split("x", 1)
|
||||
wh = (int(w_str), int(h_str))
|
||||
if wh not in seen_warp_resolutions:
|
||||
seen_warp_resolutions.add(wh)
|
||||
selected_warp_resolutions.append(wh)
|
||||
if not selected_warp_resolutions:
|
||||
selected_warp_resolutions = default_warp_resolutions
|
||||
else:
|
||||
selected_warp_resolutions = default_warp_resolutions
|
||||
|
||||
compile_warp_script = "#selfdrive/modeld/compile_warp.py"
|
||||
warp_targets = []
|
||||
# Camera resolutions required by modeld compile_warp.py
|
||||
for w, h in selected_warp_resolutions:
|
||||
warp_targets += [File(f"models/warp_{w}x{h}_tinygrad.pkl").abspath, File(f"models/dm_warp_{w}x{h}_tinygrad.pkl").abspath]
|
||||
lenv.Command(
|
||||
warp_targets,
|
||||
tinygrad_files + [compile_warp_script],
|
||||
f'{compile_warp_flags} python3 selfdrive/modeld/compile_warp.py',
|
||||
)
|
||||
else:
|
||||
print("Skipping model warp precompile (set SP_BUILD_WARP_ARTIFACTS=1 to enable)")
|
||||
|
||||
# Get model metadata
|
||||
for model_name in ['driving_vision', 'driving_policy', 'dmonitoring_model']:
|
||||
fn = File(f"models/{model_name}").abspath
|
||||
script_files = [File(Dir("#selfdrive/modeld").File("get_model_metadata.py").abspath)]
|
||||
cmd = f'python3 {Dir("#selfdrive/modeld").abspath}/get_model_metadata.py {fn}.onnx'
|
||||
lenv.Command(fn + "_metadata.pkl", [fn + ".onnx"] + tinygrad_files + script_files, cmd)
|
||||
model_rel_path = f"selfdrive/modeld/models/{model_name}"
|
||||
model_node_path = f"#{model_rel_path}"
|
||||
metadata_script = "#selfdrive/modeld/get_model_metadata.py"
|
||||
cmd = f'python3 selfdrive/modeld/get_model_metadata.py {model_rel_path}.onnx'
|
||||
lenv.Command(model_node_path + "_metadata.pkl", [model_node_path + ".onnx"] + tinygrad_files + [metadata_script], cmd)
|
||||
|
||||
def tg_compile(flags, model_name):
|
||||
pythonpath_string = 'PYTHONPATH="${PYTHONPATH}:' + env.Dir("#tinygrad_repo").abspath + '"'
|
||||
fn = File(f"models/{model_name}").abspath
|
||||
tinygrad_root = "tinygrad_repo"
|
||||
compile_script = "#tinygrad_repo/examples/openpilot/compile3.py"
|
||||
pythonpath_string = 'PYTHONPATH="${PYTHONPATH}:' + tinygrad_root + '"'
|
||||
model_rel_path = f"selfdrive/modeld/models/{model_name}"
|
||||
model_node_path = f"#{model_rel_path}"
|
||||
model_input = f"./{model_rel_path}.onnx"
|
||||
return lenv.Command(
|
||||
fn + "_tinygrad.pkl",
|
||||
[fn + ".onnx"] + tinygrad_files,
|
||||
f'{pythonpath_string} {flags} python3 {Dir("#tinygrad_repo").abspath}/examples/openpilot/compile3.py {fn}.onnx {fn}_tinygrad.pkl'
|
||||
model_node_path + "_tinygrad.pkl",
|
||||
[model_node_path + ".onnx"] + tinygrad_files + [compile_script],
|
||||
f'{pythonpath_string} {flags} python3 tinygrad_repo/examples/openpilot/compile3.py {model_input} {model_rel_path}_tinygrad.pkl'
|
||||
)
|
||||
|
||||
compile_model_tinygrad_pkl = build_model_tinygrad_pkl or allow_host_tinygrad_pkl
|
||||
if not compile_model_tinygrad_pkl:
|
||||
print("Skipping tinygrad model PKL compile (set SP_BUILD_MODEL_TINYGRAD_PKL=1 or SP_ALLOW_HOST_TINYGRAD_PKL=1 to enable)")
|
||||
|
||||
# Compile small models
|
||||
for model_name in ['driving_vision', 'driving_policy', 'dmonitoring_model']:
|
||||
flags = {
|
||||
'larch64': 'DEV=QCOM FLOAT16=1 NOLOCALS=1 IMAGE=2 JIT_BATCH_SIZE=0',
|
||||
'Darwin': f'DEV=CPU HOME={os.path.expanduser("~")}', # tinygrad calls brew which needs a $HOME in the env
|
||||
}.get(arch, 'DEV=CPU CPU_LLVM=1')
|
||||
if model_name == 'dmonitoring_model' and skip_dm_tinygrad_pkl:
|
||||
print("Skipping dmonitoring_model_tinygrad.pkl compile (SP_SKIP_DM_TINYGRAD_PKL enabled)")
|
||||
continue
|
||||
if not compile_model_tinygrad_pkl:
|
||||
continue
|
||||
if arch == 'larch64':
|
||||
# On real devices keep QCOM codegen.
|
||||
flags = 'DEV=QCOM QCOM=1 FLOAT16=1 NOLOCALS=1 IMAGE=2 JIT_BATCH_SIZE=0 DEBUG=0'
|
||||
else:
|
||||
# Opt-in host compile (for debugging only).
|
||||
flags = {
|
||||
'Darwin': 'DEV=CPU CPU=1 IMAGE=0 NOLOCALS=1 DEBUG=0 HOME=/tmp',
|
||||
}.get(arch, 'DEV=CPU CPU=1 IMAGE=0 NOLOCALS=1 DEBUG=0')
|
||||
tg_compile(flags, model_name)
|
||||
|
||||
# Compile BIG model if USB GPU is available
|
||||
@@ -62,7 +127,7 @@ if "USBGPU" in os.environ:
|
||||
devs = subprocess.check_output('python3 -c "from tinygrad import Device; print(list(Device.get_available_devices()))"', shell=True, cwd=env.Dir('#').abspath)
|
||||
if b"AMD" in devs:
|
||||
print("USB GPU detected... building")
|
||||
flags = "DEV=AMD AMD_IFACE=USB AMD_LLVM=1 NOLOCALS=0 IMAGE=0"
|
||||
flags = "DEV=AMD AMD=1 AMD_IFACE=USB AMD_LLVM=1 NOLOCALS=0 IMAGE=0 DEBUG=0"
|
||||
bp = tg_compile(flags, "big_driving_policy")
|
||||
bv = tg_compile(flags, "big_driving_vision")
|
||||
lenv.SideEffect('lock', [bp, bv]) # tg doesn't support multi-process so build serially
|
||||
|
||||
@@ -0,0 +1,242 @@
|
||||
#!/usr/bin/env python3
|
||||
import os
|
||||
import time
|
||||
import pickle
|
||||
import numpy as np
|
||||
from pathlib import Path
|
||||
from tinygrad.tensor import Tensor
|
||||
from tinygrad.helpers import Context
|
||||
from tinygrad.device import Device
|
||||
from tinygrad.engine.jit import TinyJit
|
||||
|
||||
from openpilot.system.camerad.cameras.nv12_info import get_nv12_info
|
||||
|
||||
MODELS_DIR = Path(__file__).parent / 'models'
|
||||
WARP_COMPILE_ITERS = max(2, int(os.getenv("WARP_COMPILE_ITERS", "2")))
|
||||
|
||||
# Keep compile_warp standalone so it does not depend on common.transformations C extensions.
|
||||
MEDMODEL_INPUT_SIZE = (512, 256)
|
||||
DM_INPUT_SIZE = (1440, 960)
|
||||
|
||||
DEFAULT_CAMERA_CONFIGS = [
|
||||
(1928, 1208), # tici / tizi
|
||||
(1344, 760), # mici
|
||||
]
|
||||
|
||||
|
||||
def _parse_camera_configs_from_env() -> list[tuple[int, int]]:
|
||||
raw = os.getenv("SP_WARP_RESOLUTIONS", "").strip()
|
||||
if not raw:
|
||||
return DEFAULT_CAMERA_CONFIGS
|
||||
|
||||
parsed: list[tuple[int, int]] = []
|
||||
for token in raw.replace(";", ",").split(","):
|
||||
token = token.strip().lower()
|
||||
if not token:
|
||||
continue
|
||||
try:
|
||||
w_str, h_str = token.split("x", 1)
|
||||
parsed.append((int(w_str), int(h_str)))
|
||||
except Exception as e:
|
||||
raise ValueError(f"Invalid SP_WARP_RESOLUTIONS token: {token!r}") from e
|
||||
|
||||
# Keep first occurrence order, drop duplicates.
|
||||
deduped: list[tuple[int, int]] = []
|
||||
seen: set[tuple[int, int]] = set()
|
||||
for wh in parsed:
|
||||
if wh not in seen:
|
||||
seen.add(wh)
|
||||
deduped.append(wh)
|
||||
return deduped or DEFAULT_CAMERA_CONFIGS
|
||||
|
||||
|
||||
CAMERA_CONFIGS = _parse_camera_configs_from_env()
|
||||
|
||||
UV_SCALE_MATRIX = np.array([[0.5, 0, 0], [0, 0.5, 0], [0, 0, 1]], dtype=np.float32)
|
||||
UV_SCALE_MATRIX_INV = np.linalg.inv(UV_SCALE_MATRIX)
|
||||
|
||||
IMG_BUFFER_SHAPE = (30, MEDMODEL_INPUT_SIZE[1] // 2, MEDMODEL_INPUT_SIZE[0] // 2)
|
||||
|
||||
|
||||
def warp_pkl_path(w, h):
|
||||
return MODELS_DIR / f'warp_{w}x{h}_tinygrad.pkl'
|
||||
|
||||
|
||||
def dm_warp_pkl_path(w, h):
|
||||
return MODELS_DIR / f'dm_warp_{w}x{h}_tinygrad.pkl'
|
||||
|
||||
|
||||
def warp_perspective_tinygrad(src_flat, M_inv, dst_shape, src_shape, stride_pad):
|
||||
w_dst, h_dst = dst_shape
|
||||
h_src, w_src = src_shape
|
||||
|
||||
x = Tensor.arange(w_dst).reshape(1, w_dst).expand(h_dst, w_dst).reshape(-1)
|
||||
y = Tensor.arange(h_dst).reshape(h_dst, 1).expand(h_dst, w_dst).reshape(-1)
|
||||
|
||||
# inline 3x3 matmul as elementwise to avoid reduce op (enables fusion with gather)
|
||||
src_x = M_inv[0, 0] * x + M_inv[0, 1] * y + M_inv[0, 2]
|
||||
src_y = M_inv[1, 0] * x + M_inv[1, 1] * y + M_inv[1, 2]
|
||||
src_w = M_inv[2, 0] * x + M_inv[2, 1] * y + M_inv[2, 2]
|
||||
|
||||
src_x = src_x / src_w
|
||||
src_y = src_y / src_w
|
||||
|
||||
x_nn_clipped = Tensor.round(src_x).clip(0, w_src - 1).cast('int')
|
||||
y_nn_clipped = Tensor.round(src_y).clip(0, h_src - 1).cast('int')
|
||||
idx = y_nn_clipped * (w_src + stride_pad) + x_nn_clipped
|
||||
|
||||
return src_flat[idx]
|
||||
|
||||
|
||||
def frames_to_tensor(frames, model_w, model_h):
|
||||
H = (frames.shape[0] * 2) // 3
|
||||
W = frames.shape[1]
|
||||
in_img1 = Tensor.cat(frames[0:H:2, 0::2],
|
||||
frames[1:H:2, 0::2],
|
||||
frames[0:H:2, 1::2],
|
||||
frames[1:H:2, 1::2],
|
||||
frames[H:H+H//4].reshape((H//2, W//2)),
|
||||
frames[H+H//4:H+H//2].reshape((H//2, W//2)), dim=0).reshape((6, H//2, W//2))
|
||||
return in_img1
|
||||
|
||||
|
||||
def make_frame_prepare(cam_w, cam_h, model_w, model_h):
|
||||
stride, y_height, uv_height, _ = get_nv12_info(cam_w, cam_h)
|
||||
uv_offset = stride * y_height
|
||||
stride_pad = stride - cam_w
|
||||
|
||||
def frame_prepare_tinygrad(input_frame, M_inv):
|
||||
# UV_SCALE @ M_inv @ UV_SCALE_INV simplifies to elementwise scaling
|
||||
M_inv_uv = M_inv * Tensor([[1.0, 1.0, 0.5], [1.0, 1.0, 0.5], [2.0, 2.0, 1.0]])
|
||||
# deinterleave NV12 UV plane (UVUV... -> separate U, V)
|
||||
uv = input_frame[uv_offset:uv_offset + uv_height * stride].reshape(uv_height, stride)
|
||||
with Context(SPLIT_REDUCEOP=0):
|
||||
y = warp_perspective_tinygrad(input_frame[:cam_h*stride],
|
||||
M_inv, (model_w, model_h),
|
||||
(cam_h, cam_w), stride_pad).realize()
|
||||
u = warp_perspective_tinygrad(uv[:cam_h//2, :cam_w:2].flatten(),
|
||||
M_inv_uv, (model_w//2, model_h//2),
|
||||
(cam_h//2, cam_w//2), 0).realize()
|
||||
v = warp_perspective_tinygrad(uv[:cam_h//2, 1:cam_w:2].flatten(),
|
||||
M_inv_uv, (model_w//2, model_h//2),
|
||||
(cam_h//2, cam_w//2), 0).realize()
|
||||
yuv = y.cat(u).cat(v).reshape((model_h * 3 // 2, model_w))
|
||||
tensor = frames_to_tensor(yuv, model_w, model_h)
|
||||
return tensor
|
||||
return frame_prepare_tinygrad
|
||||
|
||||
|
||||
def make_update_img_input(frame_prepare, model_w, model_h):
|
||||
def update_img_input_tinygrad(tensor, frame, M_inv):
|
||||
M_inv = M_inv.to(Device.DEFAULT)
|
||||
new_img = frame_prepare(frame, M_inv)
|
||||
full_buffer = tensor[6:].cat(new_img, dim=0).contiguous()
|
||||
return full_buffer, Tensor.cat(full_buffer[:6], full_buffer[-6:], dim=0).contiguous().reshape(1, 12, model_h//2, model_w//2)
|
||||
return update_img_input_tinygrad
|
||||
|
||||
|
||||
def make_update_both_imgs(frame_prepare, model_w, model_h):
|
||||
update_img = make_update_img_input(frame_prepare, model_w, model_h)
|
||||
|
||||
def update_both_imgs_tinygrad(calib_img_buffer, new_img, M_inv,
|
||||
calib_big_img_buffer, new_big_img, M_inv_big):
|
||||
calib_img_buffer, calib_img_pair = update_img(calib_img_buffer, new_img, M_inv)
|
||||
calib_big_img_buffer, calib_big_img_pair = update_img(calib_big_img_buffer, new_big_img, M_inv_big)
|
||||
return calib_img_buffer, calib_img_pair, calib_big_img_buffer, calib_big_img_pair
|
||||
return update_both_imgs_tinygrad
|
||||
|
||||
|
||||
def make_warp_dm(cam_w, cam_h, dm_w, dm_h):
|
||||
stride, y_height, _, _ = get_nv12_info(cam_w, cam_h)
|
||||
stride_pad = stride - cam_w
|
||||
|
||||
def warp_dm(input_frame, M_inv):
|
||||
M_inv = M_inv.to(Device.DEFAULT)
|
||||
result = warp_perspective_tinygrad(input_frame[:cam_h*stride], M_inv, (dm_w, dm_h), (cam_h, cam_w), stride_pad).reshape(-1, dm_h * dm_w)
|
||||
return result
|
||||
return warp_dm
|
||||
|
||||
|
||||
def compile_modeld_warp(cam_w, cam_h):
|
||||
model_w, model_h = MEDMODEL_INPUT_SIZE
|
||||
_, _, _, yuv_size = get_nv12_info(cam_w, cam_h)
|
||||
|
||||
print(f"Compiling modeld warp for {cam_w}x{cam_h} ({WARP_COMPILE_ITERS} iters)...", flush=True)
|
||||
|
||||
frame_prepare = make_frame_prepare(cam_w, cam_h, model_w, model_h)
|
||||
update_both_imgs = make_update_both_imgs(frame_prepare, model_w, model_h)
|
||||
update_img_jit = TinyJit(update_both_imgs, prune=True)
|
||||
|
||||
full_buffer = Tensor.zeros(IMG_BUFFER_SHAPE, dtype='uint8').contiguous().realize()
|
||||
big_full_buffer = Tensor.zeros(IMG_BUFFER_SHAPE, dtype='uint8').contiguous().realize()
|
||||
full_buffer_np = np.zeros(IMG_BUFFER_SHAPE, dtype=np.uint8)
|
||||
big_full_buffer_np = np.zeros(IMG_BUFFER_SHAPE, dtype=np.uint8)
|
||||
|
||||
for i in range(WARP_COMPILE_ITERS):
|
||||
new_frame_np = (32 * np.random.randn(yuv_size).astype(np.float32) + 128).clip(0, 255).astype(np.uint8)
|
||||
img_inputs = [full_buffer,
|
||||
Tensor.from_blob(new_frame_np.ctypes.data, (yuv_size,), dtype='uint8').realize(),
|
||||
Tensor(Tensor.randn(3, 3).mul(8).realize().numpy(), device='NPY')]
|
||||
new_big_frame_np = (32 * np.random.randn(yuv_size).astype(np.float32) + 128).clip(0, 255).astype(np.uint8)
|
||||
big_img_inputs = [big_full_buffer,
|
||||
Tensor.from_blob(new_big_frame_np.ctypes.data, (yuv_size,), dtype='uint8').realize(),
|
||||
Tensor(Tensor.randn(3, 3).mul(8).realize().numpy(), device='NPY')]
|
||||
inputs = img_inputs + big_img_inputs
|
||||
Device.default.synchronize()
|
||||
|
||||
inputs_np = [x.numpy() for x in inputs]
|
||||
inputs_np[0] = full_buffer_np
|
||||
inputs_np[3] = big_full_buffer_np
|
||||
|
||||
st = time.perf_counter()
|
||||
out = update_img_jit(*inputs)
|
||||
full_buffer = out[0].contiguous().realize().clone()
|
||||
big_full_buffer = out[2].contiguous().realize().clone()
|
||||
mt = time.perf_counter()
|
||||
Device.default.synchronize()
|
||||
et = time.perf_counter()
|
||||
print(f" [{i+1}/{WARP_COMPILE_ITERS}] enqueue {(mt-st)*1e3:6.2f} ms -- total {(et-st)*1e3:6.2f} ms", flush=True)
|
||||
|
||||
pkl_path = warp_pkl_path(cam_w, cam_h)
|
||||
with open(pkl_path, "wb") as f:
|
||||
pickle.dump(update_img_jit, f)
|
||||
print(f" Saved to {pkl_path}", flush=True)
|
||||
|
||||
jit = pickle.load(open(pkl_path, "rb"))
|
||||
jit(*inputs)
|
||||
|
||||
|
||||
def compile_dm_warp(cam_w, cam_h):
|
||||
dm_w, dm_h = DM_INPUT_SIZE
|
||||
_, _, _, yuv_size = get_nv12_info(cam_w, cam_h)
|
||||
|
||||
print(f"Compiling DM warp for {cam_w}x{cam_h} ({WARP_COMPILE_ITERS} iters)...", flush=True)
|
||||
|
||||
warp_dm = make_warp_dm(cam_w, cam_h, dm_w, dm_h)
|
||||
warp_dm_jit = TinyJit(warp_dm, prune=True)
|
||||
|
||||
for i in range(WARP_COMPILE_ITERS):
|
||||
inputs = [Tensor.from_blob((32 * Tensor.randn(yuv_size,) + 128).cast(dtype='uint8').realize().numpy().ctypes.data, (yuv_size,), dtype='uint8'),
|
||||
Tensor(Tensor.randn(3, 3).mul(8).realize().numpy(), device='NPY')]
|
||||
Device.default.synchronize()
|
||||
st = time.perf_counter()
|
||||
warp_dm_jit(*inputs)
|
||||
mt = time.perf_counter()
|
||||
Device.default.synchronize()
|
||||
et = time.perf_counter()
|
||||
print(f" [{i+1}/{WARP_COMPILE_ITERS}] enqueue {(mt-st)*1e3:6.2f} ms -- total {(et-st)*1e3:6.2f} ms", flush=True)
|
||||
|
||||
pkl_path = dm_warp_pkl_path(cam_w, cam_h)
|
||||
with open(pkl_path, "wb") as f:
|
||||
pickle.dump(warp_dm_jit, f)
|
||||
print(f" Saved to {pkl_path}", flush=True)
|
||||
|
||||
|
||||
def run_and_save_pickle():
|
||||
for cam_w, cam_h in CAMERA_CONFIGS:
|
||||
compile_modeld_warp(cam_w, cam_h)
|
||||
compile_dm_warp(cam_w, cam_h)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
run_and_save_pickle()
|
||||
@@ -3,7 +3,6 @@ import os
|
||||
from openpilot.system.hardware import TICI
|
||||
os.environ['DEV'] = 'QCOM' if TICI else 'CPU'
|
||||
from tinygrad.tensor import Tensor
|
||||
from tinygrad.dtype import dtypes
|
||||
import time
|
||||
import pickle
|
||||
import numpy as np
|
||||
@@ -16,50 +15,109 @@ from openpilot.common.swaglog import cloudlog
|
||||
from openpilot.common.realtime import config_realtime_process
|
||||
from openpilot.common.transformations.model import dmonitoringmodel_intrinsics
|
||||
from openpilot.common.transformations.camera import _ar_ox_fisheye, _os_fisheye
|
||||
from openpilot.selfdrive.modeld.models.commonmodel_pyx import CLContext, MonitoringModelFrame
|
||||
from openpilot.system.camerad.cameras.nv12_info import get_nv12_info
|
||||
from openpilot.common.file_chunker import read_file_chunked
|
||||
from openpilot.selfdrive.modeld.parse_model_outputs import sigmoid, safe_exp
|
||||
from openpilot.selfdrive.modeld.runners.tinygrad_helpers import qcom_tensor_from_opencl_address
|
||||
|
||||
PROCESS_NAME = "selfdrive.modeld.dmonitoringmodeld"
|
||||
SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')
|
||||
MODEL_PKL_PATH = Path(__file__).parent / 'models/dmonitoring_model_tinygrad.pkl'
|
||||
METADATA_PATH = Path(__file__).parent / 'models/dmonitoring_model_metadata.pkl'
|
||||
MODELS_DIR = Path(__file__).parent / 'models'
|
||||
|
||||
|
||||
class ModelState:
|
||||
inputs: dict[str, np.ndarray]
|
||||
output: np.ndarray
|
||||
|
||||
def __init__(self, cl_ctx):
|
||||
def __init__(self):
|
||||
with open(METADATA_PATH, 'rb') as f:
|
||||
model_metadata = pickle.load(f)
|
||||
self.input_shapes = model_metadata['input_shapes']
|
||||
self.output_slices = model_metadata['output_slices']
|
||||
|
||||
self.frame = MonitoringModelFrame(cl_ctx)
|
||||
self.numpy_inputs = {
|
||||
'calib': np.zeros(self.input_shapes['calib'], dtype=np.float32),
|
||||
}
|
||||
|
||||
self.warp_inputs_np = {'transform': np.zeros((3,3), dtype=np.float32)}
|
||||
self.warp_inputs = {k: Tensor(v, device='NPY') for k,v in self.warp_inputs_np.items()}
|
||||
self.frame_buf_params = None
|
||||
self.tensor_inputs = {k: Tensor(v, device='NPY').realize() for k,v in self.numpy_inputs.items()}
|
||||
with open(MODEL_PKL_PATH, "rb") as f:
|
||||
self.model_run = pickle.load(f)
|
||||
self._blob_cache : dict[int, Tensor] = {}
|
||||
self.image_warp = None
|
||||
self._warp_rebuild_attempted: set[tuple[int, int]] = set()
|
||||
self._warp_backend_rebuild_attempted: set[tuple[int, int]] = set()
|
||||
self.model_run = pickle.loads(read_file_chunked(str(MODEL_PKL_PATH)))
|
||||
|
||||
def _load_or_rebuild_dm_warp(self, width: int, height: int):
|
||||
warp_path = MODELS_DIR / f'dm_warp_{width}x{height}_tinygrad.pkl'
|
||||
resolution_key = (width, height)
|
||||
|
||||
def load_warp():
|
||||
with open(warp_path, "rb") as f:
|
||||
return pickle.load(f)
|
||||
|
||||
try:
|
||||
return load_warp()
|
||||
except Exception as error:
|
||||
if resolution_key in self._warp_rebuild_attempted:
|
||||
raise
|
||||
|
||||
self._warp_rebuild_attempted.add(resolution_key)
|
||||
cloudlog.exception(f"Failed to load DM warp artifact {warp_path}: {error}")
|
||||
cloudlog.warning(f"Rebuilding DM warp artifact for {width}x{height}")
|
||||
|
||||
try:
|
||||
warp_path.unlink(missing_ok=True)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
from openpilot.selfdrive.modeld.compile_warp import compile_dm_warp
|
||||
compile_dm_warp(width, height)
|
||||
|
||||
try:
|
||||
return load_warp()
|
||||
except Exception as retry_error:
|
||||
cloudlog.exception(f"Reload failed after rebuilding {warp_path}: {retry_error}")
|
||||
raise
|
||||
|
||||
def run(self, buf: VisionBuf, calib: np.ndarray, transform: np.ndarray) -> tuple[np.ndarray, float]:
|
||||
self.numpy_inputs['calib'][0,:] = calib
|
||||
|
||||
t1 = time.perf_counter()
|
||||
|
||||
input_img_cl = self.frame.prepare(buf, transform.flatten())
|
||||
if TICI:
|
||||
# The imgs tensors are backed by opencl memory, only need init once
|
||||
if 'input_img' not in self.tensor_inputs:
|
||||
self.tensor_inputs['input_img'] = qcom_tensor_from_opencl_address(input_img_cl.mem_address, self.input_shapes['input_img'], dtype=dtypes.uint8)
|
||||
else:
|
||||
self.tensor_inputs['input_img'] = Tensor(self.frame.buffer_from_cl(input_img_cl).reshape(self.input_shapes['input_img']), dtype=dtypes.uint8).realize()
|
||||
if self.image_warp is None:
|
||||
self.frame_buf_params = get_nv12_info(buf.width, buf.height)
|
||||
self.image_warp = self._load_or_rebuild_dm_warp(buf.width, buf.height)
|
||||
ptr = buf.data.ctypes.data
|
||||
# There is a ringbuffer of imgs, just cache tensors pointing to all of them
|
||||
if ptr not in self._blob_cache:
|
||||
self._blob_cache[ptr] = Tensor.from_blob(ptr, (self.frame_buf_params[3],), dtype='uint8')
|
||||
|
||||
self.warp_inputs_np['transform'][:] = transform[:]
|
||||
resolution_key = (buf.width, buf.height)
|
||||
try:
|
||||
self.tensor_inputs['input_img'] = self.image_warp(self._blob_cache[ptr], self.warp_inputs['transform']).realize()
|
||||
except AssertionError as error:
|
||||
# Handle runtime backend mismatch (e.g. CPU-captured warp artifact on QCOM device).
|
||||
if "args mismatch in JIT" not in str(error) or resolution_key in self._warp_backend_rebuild_attempted:
|
||||
raise
|
||||
|
||||
output = self.model_run(**self.tensor_inputs).contiguous().realize().uop.base.buffer.numpy()
|
||||
self._warp_backend_rebuild_attempted.add(resolution_key)
|
||||
cloudlog.warning(f"DM warp JIT backend mismatch for {buf.width}x{buf.height}; rebuilding artifact for active backend")
|
||||
warp_path = MODELS_DIR / f'dm_warp_{buf.width}x{buf.height}_tinygrad.pkl'
|
||||
try:
|
||||
warp_path.unlink(missing_ok=True)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
from openpilot.selfdrive.modeld.compile_warp import compile_dm_warp
|
||||
compile_dm_warp(buf.width, buf.height)
|
||||
self.image_warp = self._load_or_rebuild_dm_warp(buf.width, buf.height)
|
||||
self.tensor_inputs['input_img'] = self.image_warp(self._blob_cache[ptr], self.warp_inputs['transform']).realize()
|
||||
|
||||
output = self.model_run(**self.tensor_inputs).contiguous().realize().uop.base.buffer.numpy().flatten()
|
||||
|
||||
t2 = time.perf_counter()
|
||||
return output, t2 - t1
|
||||
@@ -107,12 +165,11 @@ def get_driverstate_packet(model_output, frame_id: int, location_ts: int, exec_t
|
||||
def main():
|
||||
config_realtime_process(7, 5)
|
||||
|
||||
cl_context = CLContext()
|
||||
model = ModelState(cl_context)
|
||||
model = ModelState()
|
||||
cloudlog.warning("models loaded, dmonitoringmodeld starting")
|
||||
|
||||
cloudlog.warning("connecting to driver stream")
|
||||
vipc_client = VisionIpcClient("camerad", VisionStreamType.VISION_STREAM_DRIVER, True, cl_context)
|
||||
vipc_client = VisionIpcClient("camerad", VisionStreamType.VISION_STREAM_DRIVER, True)
|
||||
while not vipc_client.connect(False):
|
||||
time.sleep(0.1)
|
||||
assert vipc_client.is_connected()
|
||||
|
||||
+45
-12
@@ -31,16 +31,47 @@ from openpilot.selfdrive.modeld.constants import ModelConstants, Plan
|
||||
from openpilot.selfdrive.modeld.models.commonmodel_pyx import DrivingModelFrame, CLContext
|
||||
from openpilot.selfdrive.modeld.runners.tinygrad_helpers import qcom_tensor_from_opencl_address
|
||||
|
||||
from openpilot.frogpilot.common.frogpilot_variables import get_frogpilot_toggles
|
||||
from openpilot.frogpilot.common.frogpilot_variables import MODELS_PATH, get_frogpilot_toggles
|
||||
|
||||
|
||||
PROCESS_NAME = "selfdrive.modeld.modeld"
|
||||
SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')
|
||||
|
||||
VISION_PKL_PATH = Path(__file__).parent / 'models/driving_vision_tinygrad.pkl'
|
||||
POLICY_PKL_PATH = Path(__file__).parent / 'models/driving_policy_tinygrad.pkl'
|
||||
VISION_METADATA_PATH = Path(__file__).parent / 'models/driving_vision_metadata.pkl'
|
||||
POLICY_METADATA_PATH = Path(__file__).parent / 'models/driving_policy_metadata.pkl'
|
||||
BUILTIN_MODEL_DIR = Path(__file__).parent / "models"
|
||||
BUILTIN_VISION_PKL_PATH = BUILTIN_MODEL_DIR / "driving_vision_tinygrad.pkl"
|
||||
BUILTIN_POLICY_PKL_PATH = BUILTIN_MODEL_DIR / "driving_policy_tinygrad.pkl"
|
||||
BUILTIN_VISION_METADATA_PATH = BUILTIN_MODEL_DIR / "driving_vision_metadata.pkl"
|
||||
BUILTIN_POLICY_METADATA_PATH = BUILTIN_MODEL_DIR / "driving_policy_metadata.pkl"
|
||||
|
||||
|
||||
def _decode_param(value) -> str:
|
||||
if isinstance(value, bytes):
|
||||
return value.decode("utf-8")
|
||||
return str(value or "")
|
||||
|
||||
|
||||
def _resolve_model_paths(params: Params) -> tuple[str, dict[str, Path]]:
|
||||
model_key = _decode_param(params.get("DrivingModel")).strip()
|
||||
candidates = [model_key] if model_key else []
|
||||
if model_key.endswith("_default"):
|
||||
candidates.append(model_key[:-8])
|
||||
|
||||
for candidate in candidates:
|
||||
files = {
|
||||
"vision_pkl": MODELS_PATH / f"{candidate}_driving_vision_tinygrad.pkl",
|
||||
"policy_pkl": MODELS_PATH / f"{candidate}_driving_policy_tinygrad.pkl",
|
||||
"vision_meta": MODELS_PATH / f"{candidate}_driving_vision_metadata.pkl",
|
||||
"policy_meta": MODELS_PATH / f"{candidate}_driving_policy_metadata.pkl",
|
||||
}
|
||||
if all(path.is_file() for path in files.values()):
|
||||
return candidate, files
|
||||
|
||||
return "builtin", {
|
||||
"vision_pkl": BUILTIN_VISION_PKL_PATH,
|
||||
"policy_pkl": BUILTIN_POLICY_PKL_PATH,
|
||||
"vision_meta": BUILTIN_VISION_METADATA_PATH,
|
||||
"policy_meta": BUILTIN_POLICY_METADATA_PATH,
|
||||
}
|
||||
|
||||
LAT_SMOOTH_SECONDS = 0.0
|
||||
LONG_SMOOTH_SECONDS = 0.3
|
||||
@@ -143,15 +174,15 @@ class ModelState:
|
||||
output: np.ndarray
|
||||
prev_desire: np.ndarray # for tracking the rising edge of the pulse
|
||||
|
||||
def __init__(self, context: CLContext):
|
||||
with open(VISION_METADATA_PATH, 'rb') as f:
|
||||
def __init__(self, context: CLContext, model_paths: dict[str, Path]):
|
||||
with open(model_paths["vision_meta"], 'rb') as f:
|
||||
vision_metadata = pickle.load(f)
|
||||
self.vision_input_shapes = vision_metadata['input_shapes']
|
||||
self.vision_input_names = list(self.vision_input_shapes.keys())
|
||||
self.vision_output_slices = vision_metadata['output_slices']
|
||||
vision_output_size = vision_metadata['output_shapes']['outputs'][1]
|
||||
|
||||
with open(POLICY_METADATA_PATH, 'rb') as f:
|
||||
with open(model_paths["policy_meta"], 'rb') as f:
|
||||
policy_metadata = pickle.load(f)
|
||||
self.policy_input_shapes = policy_metadata['input_shapes']
|
||||
self.policy_output_slices = policy_metadata['output_slices']
|
||||
@@ -174,10 +205,10 @@ class ModelState:
|
||||
self.policy_output = np.zeros(policy_output_size, dtype=np.float32)
|
||||
self.parser = Parser()
|
||||
|
||||
with open(VISION_PKL_PATH, "rb") as f:
|
||||
with open(model_paths["vision_pkl"], "rb") as f:
|
||||
self.vision_run = pickle.load(f)
|
||||
|
||||
with open(POLICY_PKL_PATH, "rb") as f:
|
||||
with open(model_paths["policy_pkl"], "rb") as f:
|
||||
self.policy_run = pickle.load(f)
|
||||
|
||||
def slice_outputs(self, model_outputs: np.ndarray, output_slices: dict[str, slice]) -> dict[str, np.ndarray]:
|
||||
@@ -238,8 +269,11 @@ def main(demo=False):
|
||||
st = time.monotonic()
|
||||
cloudlog.warning("setting up CL context")
|
||||
cl_context = CLContext()
|
||||
params = Params()
|
||||
selected_model_key, model_paths = _resolve_model_paths(params)
|
||||
cloudlog.warning("CL context ready; loading model")
|
||||
model = ModelState(cl_context)
|
||||
model = ModelState(cl_context, model_paths)
|
||||
cloudlog.warning(f"selected model source: {selected_model_key}")
|
||||
cloudlog.warning(f"models loaded in {time.monotonic() - st:.1f}s, modeld starting")
|
||||
|
||||
# visionipc clients
|
||||
@@ -270,7 +304,6 @@ def main(demo=False):
|
||||
sm = SubMaster(["deviceState", "carState", "roadCameraState", "liveCalibration", "driverMonitoringState", "carControl", "liveDelay"])
|
||||
|
||||
publish_state = PublishState()
|
||||
params = Params()
|
||||
|
||||
# setup filter to track dropped frames
|
||||
frame_dropped_filter = FirstOrderFilter(0., 10., 1. / ModelConstants.MODEL_RUN_FREQ)
|
||||
|
||||
Executable
BIN
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
@@ -1,3 +1,2 @@
|
||||
pandad
|
||||
pandad_api_impl.cpp
|
||||
tests/test_pandad_usbprotocol
|
||||
|
||||
@@ -137,7 +137,7 @@ std::optional<std::string> Panda::get_serial() {
|
||||
|
||||
bool Panda::up_to_date() {
|
||||
if (auto fw_sig = get_firmware_version()) {
|
||||
for (auto fn : { "panda.bin.signed", "panda_h7.bin.signed" }) {
|
||||
for (auto fn : { "panda.bin.signed", "panda_h7.bin.signed", "panda_remote.bin.signed", "panda_h7_remote.bin.signed" }) {
|
||||
auto content = util::read_file(std::string("../../panda/board/obj/") + fn);
|
||||
if (content.size() >= fw_sig->size() &&
|
||||
memcmp(content.data() + content.size() - fw_sig->size(), fw_sig->data(), fw_sig->size()) == 0) {
|
||||
|
||||
Executable
BIN
Binary file not shown.
@@ -8,20 +8,39 @@ import subprocess
|
||||
|
||||
from panda import Panda, PandaDFU, PandaProtocolMismatch, FW_PATH
|
||||
from openpilot.common.basedir import BASEDIR
|
||||
from openpilot.common.params import Params
|
||||
from openpilot.common.params import Params, UnknownKeyName
|
||||
from openpilot.system.hardware import HARDWARE
|
||||
from openpilot.common.swaglog import cloudlog
|
||||
|
||||
|
||||
def get_expected_signature(panda: Panda) -> bytes:
|
||||
def get_expected_firmware_path(panda: Panda, remote_start: bool) -> str:
|
||||
app_fn = panda.get_mcu_type().config.app_fn
|
||||
if remote_start:
|
||||
remote_fn = "panda_h7_remote.bin.signed" if app_fn == "panda_h7.bin.signed" else "panda_remote.bin.signed"
|
||||
remote_path = os.path.join(FW_PATH, remote_fn)
|
||||
if os.path.isfile(remote_path):
|
||||
return remote_path
|
||||
cloudlog.warning(f"Remote-start panda firmware not found: {remote_path}, falling back to default")
|
||||
return os.path.join(FW_PATH, app_fn)
|
||||
|
||||
|
||||
def get_expected_signature(panda: Panda, remote_start: bool) -> bytes:
|
||||
try:
|
||||
fn = os.path.join(FW_PATH, panda.get_mcu_type().config.app_fn)
|
||||
fn = get_expected_firmware_path(panda, remote_start)
|
||||
return Panda.get_signature_from_firmware(fn)
|
||||
except Exception:
|
||||
cloudlog.exception("Error computing expected signature")
|
||||
return b""
|
||||
|
||||
def flash_panda(panda_serial: str) -> Panda:
|
||||
|
||||
def get_remote_start_boots_comma(params: Params) -> bool:
|
||||
try:
|
||||
return params.get_bool("RemoteStartBootsComma")
|
||||
except UnknownKeyName:
|
||||
return False
|
||||
|
||||
|
||||
def flash_panda(panda_serial: str, remote_start: bool) -> Panda:
|
||||
try:
|
||||
panda = Panda(panda_serial)
|
||||
except PandaProtocolMismatch:
|
||||
@@ -29,7 +48,8 @@ def flash_panda(panda_serial: str) -> Panda:
|
||||
HARDWARE.recover_internal_panda()
|
||||
raise
|
||||
|
||||
fw_signature = get_expected_signature(panda)
|
||||
fw_path = get_expected_firmware_path(panda, remote_start)
|
||||
fw_signature = get_expected_signature(panda, remote_start)
|
||||
internal_panda = panda.is_internal()
|
||||
|
||||
panda_version = "bootstub" if panda.bootstub else panda.get_version()
|
||||
@@ -38,7 +58,7 @@ def flash_panda(panda_serial: str) -> Panda:
|
||||
|
||||
if panda.bootstub or panda_signature != fw_signature:
|
||||
cloudlog.info("Panda firmware out of date, update required")
|
||||
panda.flash()
|
||||
panda.flash(fn=fw_path)
|
||||
cloudlog.info("Done flashing")
|
||||
|
||||
if panda.bootstub:
|
||||
@@ -112,8 +132,9 @@ def main() -> None:
|
||||
|
||||
# Flash pandas
|
||||
pandas: list[Panda] = []
|
||||
remote_start = get_remote_start_boots_comma(params)
|
||||
for serial in panda_serials:
|
||||
pandas.append(flash_panda(serial))
|
||||
pandas.append(flash_panda(serial, remote_start))
|
||||
|
||||
# Ensure internal panda is present if expected
|
||||
internal_pandas = [panda for panda in pandas if panda.is_internal()]
|
||||
@@ -165,6 +186,10 @@ def main() -> None:
|
||||
first_run = False
|
||||
|
||||
# run pandad with all connected serials as arguments
|
||||
if get_remote_start_boots_comma(params):
|
||||
os.environ["BOARDD_SKIP_FW_CHECK"] = "1"
|
||||
else:
|
||||
os.environ.pop("BOARDD_SKIP_FW_CHECK", None)
|
||||
os.environ['MANAGER_DAEMON'] = 'pandad'
|
||||
process = subprocess.Popen(["./pandad", *panda_serials], cwd=os.path.join(BASEDIR, "selfdrive/pandad"))
|
||||
process.wait()
|
||||
|
||||
@@ -0,0 +1,8 @@
|
||||
"""Compatibility alias for legacy/misspelled imports.
|
||||
|
||||
Prefer: openpilot.selfdrive.pandad.pandad_api_impl
|
||||
"""
|
||||
|
||||
from openpilot.selfdrive.pandad.pandad_api_impl import can_capnp_to_list, can_list_to_can_capnp
|
||||
|
||||
__all__ = ["can_list_to_can_capnp", "can_capnp_to_list"]
|
||||
Executable
BIN
Binary file not shown.
@@ -0,0 +1,8 @@
|
||||
"""Compatibility alias for legacy imports.
|
||||
|
||||
Prefer: openpilot.selfdrive.pandad.pandad_api_impl
|
||||
"""
|
||||
|
||||
from openpilot.selfdrive.pandad.pandad_api_impl import can_capnp_to_list, can_list_to_can_capnp
|
||||
|
||||
__all__ = ["can_list_to_can_capnp", "can_capnp_to_list"]
|
||||
@@ -228,7 +228,7 @@ class SelfdriveD:
|
||||
# body always wants to enable
|
||||
self.events.add(EventName.pcmEnable)
|
||||
|
||||
# Disable on rising edge of accelerator or brake. Also disable on brake when speed > 0
|
||||
# Disable on rising edge of accelerator or brake. Also disable on brake when speed > 0.
|
||||
if (CS.gasPressed and not self.CS_prev.gasPressed and self.disengage_on_accelerator) or \
|
||||
(CS.brakePressed and (not self.CS_prev.brakePressed or not CS.standstill)) or \
|
||||
(CS.regenBraking and (not self.CS_prev.regenBraking or not CS.standstill)):
|
||||
@@ -299,15 +299,16 @@ class SelfdriveD:
|
||||
else:
|
||||
self.events.add(EventName.laneChangeBlocked)
|
||||
else:
|
||||
# Keep pre-lane-change prompts visible even when lane-width gate blocks the maneuver.
|
||||
# This preserves the onroad "Changing lanes" guidance while still surfacing
|
||||
# "No Lane Available" when the configured width threshold is not met.
|
||||
if direction == LaneChangeDirection.left:
|
||||
if self.sm['frogpilotPlan'].laneWidthLeft >= self.frogpilot_toggles.lane_detection_width:
|
||||
self.events.add(EventName.preLaneChangeLeft)
|
||||
else:
|
||||
self.events.add(EventName.preLaneChangeLeft)
|
||||
if self.sm['frogpilotPlan'].laneWidthLeft < self.frogpilot_toggles.lane_detection_width:
|
||||
self.frogpilot_events.add(FrogPilotEventName.noLaneAvailable)
|
||||
else:
|
||||
if self.sm['frogpilotPlan'].laneWidthRight >= self.frogpilot_toggles.lane_detection_width:
|
||||
self.events.add(EventName.preLaneChangeRight)
|
||||
else:
|
||||
elif direction == LaneChangeDirection.right:
|
||||
self.events.add(EventName.preLaneChangeRight)
|
||||
if self.sm['frogpilotPlan'].laneWidthRight < self.frogpilot_toggles.lane_detection_width:
|
||||
self.frogpilot_events.add(FrogPilotEventName.noLaneAvailable)
|
||||
elif self.sm['modelV2'].meta.laneChangeState in (LaneChangeState.laneChangeStarting,
|
||||
LaneChangeState.laneChangeFinishing):
|
||||
|
||||
@@ -5,12 +5,14 @@ base_libs = [common, messaging, visionipc, transformations,
|
||||
'm', 'OpenCL', 'ssl', 'crypto', 'pthread'] + qt_env["LIBS"]
|
||||
|
||||
# FrogPilot variables
|
||||
base_libs += ['avcodec', 'avformat', 'avutil', 'yuv', 'OmxCore']
|
||||
base_libs += ['avcodec', 'avformat', 'avutil', 'swresample', 'yuv', 'OmxCore']
|
||||
|
||||
if arch == 'larch64':
|
||||
base_libs.append('EGL')
|
||||
|
||||
if arch == "Darwin":
|
||||
if "OmxCore" in base_libs:
|
||||
base_libs.remove("OmxCore")
|
||||
del base_libs[base_libs.index('OpenCL')]
|
||||
qt_env['FRAMEWORKS'] += ['OpenCL']
|
||||
|
||||
@@ -44,6 +46,7 @@ qt_env['CPPPATH'] += ["../../frogpilot/ui/screenrecorder/openmax/include/"]
|
||||
|
||||
frogpilot_src = ["../../frogpilot/ui/frogpilot_ui.cc", "../../frogpilot/ui/qt/offroad/data_settings.cc",
|
||||
"../../frogpilot/ui/qt/offroad/device_settings.cc", "../../frogpilot/ui/qt/offroad/frogpilot_settings.cc",
|
||||
"../../frogpilot/ui/qt/offroad/expandable_multi_option_dialog.cc",
|
||||
"../../frogpilot/ui/qt/offroad/lateral_settings.cc", "../../frogpilot/ui/qt/offroad/longitudinal_settings.cc",
|
||||
"../../frogpilot/ui/qt/offroad/maps_settings.cc", "../../frogpilot/ui/qt/offroad/model_settings.cc",
|
||||
"../../frogpilot/ui/qt/offroad/navigation_settings.cc", "../../frogpilot/ui/qt/offroad/sounds_settings.cc",
|
||||
@@ -78,7 +81,8 @@ with open(File(translations_assets_src).abspath, 'w') as f:
|
||||
# build assets
|
||||
assets = "#selfdrive/assets/assets.cc"
|
||||
assets_src = "#selfdrive/assets/assets.qrc"
|
||||
qt_env.Command(assets, [assets_src, translations_assets_src], f"rcc $SOURCES -o $TARGET")
|
||||
rcc_bin = qt_env.get("SP_QT_RCC", "rcc")
|
||||
qt_env.Command(assets, [assets_src, translations_assets_src], f"{rcc_bin} $SOURCES -o $TARGET")
|
||||
qt_env.Depends(assets, Glob('#selfdrive/assets/*', exclude=[assets, assets_src, translations_assets_src, "#selfdrive/assets/assets.o"]) + [lrelease])
|
||||
asset_obj = qt_env.Object("assets", assets)
|
||||
|
||||
|
||||
@@ -144,6 +144,7 @@ int cachedFetch(const std::string &cache) {
|
||||
LOGD("Fetching with cache: %s", cache.c_str());
|
||||
|
||||
run(util::string_format("cp -rp %s %s", cache.c_str(), TMP_INSTALL_PATH).c_str());
|
||||
run(util::string_format("cd %s && git remote set-url origin %s", TMP_INSTALL_PATH, GIT_URL.c_str()).c_str());
|
||||
run(util::string_format("cd %s && git remote set-branches --add origin %s", TMP_INSTALL_PATH, migrated_branch.c_str()).c_str());
|
||||
|
||||
renderProgress(10);
|
||||
|
||||
@@ -1,6 +1,7 @@
|
||||
import pyray as rl
|
||||
from enum import IntEnum
|
||||
import cereal.messaging as messaging
|
||||
from openpilot.system.hardware import PC
|
||||
from openpilot.system.ui.lib.application import gui_app
|
||||
from openpilot.selfdrive.ui.layouts.sidebar import Sidebar, SIDEBAR_WIDTH
|
||||
from openpilot.selfdrive.ui.layouts.home import HomeLayout
|
||||
@@ -36,10 +37,12 @@ class MainLayout(Widget):
|
||||
# Set callbacks
|
||||
self._setup_callbacks()
|
||||
|
||||
# Start onboarding if terms or training not completed
|
||||
self._onboarding_window = OnboardingWindow()
|
||||
if not self._onboarding_window.completed:
|
||||
gui_app.set_modal_overlay(self._onboarding_window)
|
||||
# Skip onboarding on desktop; keep normal flow on device.
|
||||
self._onboarding_window = None
|
||||
if not PC:
|
||||
self._onboarding_window = OnboardingWindow()
|
||||
if not self._onboarding_window.completed:
|
||||
gui_app.set_modal_overlay(self._onboarding_window)
|
||||
|
||||
def _render(self, _):
|
||||
self._handle_onroad_transition()
|
||||
|
||||
@@ -25,6 +25,10 @@ DESCRIPTIONS = {
|
||||
"Enable this to switch to openpilot longitudinal control. Enabling Experimental mode is recommended when enabling openpilot longitudinal control alpha. " +
|
||||
"Changing this setting will restart openpilot if the car is powered on."
|
||||
),
|
||||
'use_prebuilt': tr_noop(
|
||||
"When enabled (default), openpilot uses prebuilt binaries at startup and skips source compilation. " +
|
||||
"Disable this if you intend to edit code and compile directly on-device."
|
||||
),
|
||||
}
|
||||
|
||||
|
||||
@@ -43,6 +47,14 @@ class DeveloperLayout(Widget):
|
||||
enabled=ui_state.is_offroad,
|
||||
)
|
||||
|
||||
self._use_prebuilt_toggle = toggle_item(
|
||||
lambda: tr("Use Prebuilt Binaries"),
|
||||
description=lambda: tr(DESCRIPTIONS["use_prebuilt"]),
|
||||
initial_state=self._params.get_bool("UsePrebuilt"),
|
||||
callback=self._on_use_prebuilt,
|
||||
enabled=ui_state.is_offroad,
|
||||
)
|
||||
|
||||
# SSH enable toggle + SSH key management
|
||||
self._ssh_toggle = toggle_item(
|
||||
lambda: tr("Enable SSH"),
|
||||
@@ -85,6 +97,7 @@ class DeveloperLayout(Widget):
|
||||
|
||||
self._scroller = Scroller([
|
||||
self._adb_toggle,
|
||||
self._use_prebuilt_toggle,
|
||||
self._ssh_toggle,
|
||||
self._ssh_keys,
|
||||
self._joystick_toggle,
|
||||
@@ -133,6 +146,7 @@ class DeveloperLayout(Widget):
|
||||
# refresh toggles from params to mirror external changes
|
||||
for key, item in (
|
||||
("AdbEnabled", self._adb_toggle),
|
||||
("UsePrebuilt", self._use_prebuilt_toggle),
|
||||
("SshEnabled", self._ssh_toggle),
|
||||
("JoystickDebugMode", self._joystick_toggle),
|
||||
("LongitudinalManeuverMode", self._long_maneuver_toggle),
|
||||
@@ -152,6 +166,9 @@ class DeveloperLayout(Widget):
|
||||
def _on_enable_ssh(self, state: bool):
|
||||
self._params.put_bool("SshEnabled", state)
|
||||
|
||||
def _on_use_prebuilt(self, state: bool):
|
||||
self._params.put_bool("UsePrebuilt", state)
|
||||
|
||||
def _on_joystick_debug_mode(self, state: bool):
|
||||
self._params.put_bool("JoystickDebugMode", state)
|
||||
self._params.put_bool("LongitudinalManeuverMode", False)
|
||||
|
||||
@@ -5,6 +5,7 @@ from collections.abc import Callable
|
||||
from openpilot.selfdrive.ui.layouts.settings.developer import DeveloperLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.device import DeviceLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.firehose import FirehoseLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.main_panel import StarPilotLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.software import SoftwareLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.toggles import TogglesLayout
|
||||
from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
|
||||
@@ -13,6 +14,7 @@ from openpilot.system.ui.lib.text_measure import measure_text_cached
|
||||
from openpilot.system.ui.lib.wifi_manager import WifiManager
|
||||
from openpilot.system.ui.widgets import Widget
|
||||
from openpilot.system.ui.widgets.network import NetworkUI
|
||||
from openpilot.common.params import Params
|
||||
|
||||
# Constants
|
||||
SIDEBAR_WIDTH = 500
|
||||
@@ -37,6 +39,7 @@ class PanelType(IntEnum):
|
||||
SOFTWARE = 3
|
||||
FIREHOSE = 4
|
||||
DEVELOPER = 5
|
||||
STARPILOT = 6
|
||||
|
||||
|
||||
@dataclass
|
||||
@@ -49,8 +52,13 @@ class PanelInfo:
|
||||
class SettingsLayout(Widget):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self._params = Params()
|
||||
self._current_panel = PanelType.DEVICE
|
||||
|
||||
# Panel depth tracking for hierarchical back navigation
|
||||
# 0 = top level (settings main), 1+ = sub-panels (FrogPilot categories)
|
||||
self._panel_depth = 0
|
||||
|
||||
# Panel configuration
|
||||
wifi_manager = WifiManager()
|
||||
wifi_manager.set_active(False)
|
||||
@@ -62,10 +70,15 @@ class SettingsLayout(Widget):
|
||||
PanelType.SOFTWARE: PanelInfo(tr_noop("Software"), SoftwareLayout()),
|
||||
PanelType.FIREHOSE: PanelInfo(tr_noop("Firehose"), FirehoseLayout()),
|
||||
PanelType.DEVELOPER: PanelInfo(tr_noop("Developer"), DeveloperLayout()),
|
||||
PanelType.STARPILOT: PanelInfo(tr_noop("StarPilot"), StarPilotLayout()),
|
||||
}
|
||||
|
||||
# Connect StarPilot depth callback for hierarchical back navigation
|
||||
self._panels[PanelType.STARPILOT].instance.set_depth_callback(self.set_panel_depth)
|
||||
self._panels[PanelType.STARPILOT].instance.set_settings_layout(self)
|
||||
|
||||
self._font_medium = gui_app.font(FontWeight.MEDIUM)
|
||||
self._close_icon = gui_app.texture("icons/close2.png", CLOSE_ICON_SIZE, CLOSE_ICON_SIZE)
|
||||
self._close_icon = gui_app.texture("icons/backspace.png", CLOSE_ICON_SIZE, CLOSE_ICON_SIZE)
|
||||
|
||||
# Callbacks
|
||||
self._close_callback: Callable | None = None
|
||||
@@ -73,6 +86,24 @@ class SettingsLayout(Widget):
|
||||
def set_callbacks(self, on_close: Callable):
|
||||
self._close_callback = on_close
|
||||
|
||||
def set_panel_depth(self, depth: int):
|
||||
self._panel_depth = depth
|
||||
|
||||
def refresh_developer_visibility(self):
|
||||
pass
|
||||
|
||||
def get_panel_depth(self) -> int:
|
||||
return self._panel_depth
|
||||
|
||||
def _handle_back_navigation(self):
|
||||
if self._panel_depth > 0:
|
||||
self._panel_depth -= 1
|
||||
if hasattr(self._panels[PanelType.STARPILOT].instance, 'navigate_back'):
|
||||
self._panels[PanelType.STARPILOT].instance.navigate_back()
|
||||
else:
|
||||
if self._close_callback:
|
||||
self._close_callback()
|
||||
|
||||
def _render(self, rect: rl.Rectangle):
|
||||
# Calculate layout
|
||||
sidebar_rect = rl.Rectangle(rect.x, rect.y, SIDEBAR_WIDTH, rect.height)
|
||||
@@ -85,20 +116,17 @@ class SettingsLayout(Widget):
|
||||
def _draw_sidebar(self, rect: rl.Rectangle):
|
||||
rl.draw_rectangle_rec(rect, SIDEBAR_COLOR)
|
||||
|
||||
# Close button
|
||||
close_btn_rect = rl.Rectangle(
|
||||
rect.x + (rect.width - CLOSE_BTN_SIZE) / 2, rect.y + 60, CLOSE_BTN_SIZE, CLOSE_BTN_SIZE
|
||||
)
|
||||
# Back/Close button - hierarchical navigation
|
||||
back_btn_rect = rl.Rectangle(rect.x + (rect.width - CLOSE_BTN_SIZE) / 2, rect.y + 60, CLOSE_BTN_SIZE, CLOSE_BTN_SIZE)
|
||||
|
||||
pressed = (rl.is_mouse_button_down(rl.MouseButton.MOUSE_BUTTON_LEFT) and
|
||||
rl.check_collision_point_rec(rl.get_mouse_position(), close_btn_rect))
|
||||
pressed = rl.is_mouse_button_down(rl.MouseButton.MOUSE_BUTTON_LEFT) and rl.check_collision_point_rec(rl.get_mouse_position(), back_btn_rect)
|
||||
close_color = CLOSE_BTN_PRESSED if pressed else CLOSE_BTN_COLOR
|
||||
rl.draw_rectangle_rounded(close_btn_rect, 1.0, 20, close_color)
|
||||
rl.draw_rectangle_rounded(back_btn_rect, 1.0, 20, close_color)
|
||||
|
||||
icon_color = rl.Color(255, 255, 255, 255) if not pressed else rl.Color(220, 220, 220, 255)
|
||||
icon_dest = rl.Rectangle(
|
||||
close_btn_rect.x + (close_btn_rect.width - self._close_icon.width) / 2,
|
||||
close_btn_rect.y + (close_btn_rect.height - self._close_icon.height) / 2,
|
||||
back_btn_rect.x + (back_btn_rect.width - self._close_icon.width) / 2,
|
||||
back_btn_rect.y + (back_btn_rect.height - self._close_icon.height) / 2,
|
||||
self._close_icon.width,
|
||||
self._close_icon.height,
|
||||
)
|
||||
@@ -111,12 +139,20 @@ class SettingsLayout(Widget):
|
||||
icon_color,
|
||||
)
|
||||
|
||||
# Store close button rect for click detection
|
||||
self._close_btn_rect = close_btn_rect
|
||||
# Store back button rect for click detection
|
||||
self._back_btn_rect = back_btn_rect
|
||||
|
||||
# Get tuning level to control Developer panel visibility
|
||||
tuning_level_str = self._params.get("TuningLevel", return_default=True, default="1")
|
||||
tuning_level = int(tuning_level_str) if tuning_level_str else 1
|
||||
|
||||
# Navigation buttons
|
||||
y = rect.y + 300
|
||||
for panel_type, panel_info in self._panels.items():
|
||||
# Hide Developer panel unless tuning level >= 3
|
||||
if panel_type == PanelType.DEVELOPER and tuning_level < 3:
|
||||
continue
|
||||
|
||||
button_rect = rl.Rectangle(rect.x + 50, y, rect.width - 150, NAV_BTN_HEIGHT)
|
||||
|
||||
# Button styling
|
||||
@@ -125,9 +161,7 @@ class SettingsLayout(Widget):
|
||||
# Draw button text (right-aligned)
|
||||
panel_name = tr(panel_info.name)
|
||||
text_size = measure_text_cached(self._font_medium, panel_name, 65)
|
||||
text_pos = rl.Vector2(
|
||||
button_rect.x + button_rect.width - text_size.x, button_rect.y + (button_rect.height - text_size.y) / 2
|
||||
)
|
||||
text_pos = rl.Vector2(button_rect.x + button_rect.width - text_size.x, button_rect.y + (button_rect.height - text_size.y) / 2)
|
||||
rl.draw_text_ex(self._font_medium, panel_name, text_pos, 65, 0, text_color)
|
||||
|
||||
# Store button rect for click detection
|
||||
@@ -136,9 +170,7 @@ class SettingsLayout(Widget):
|
||||
y += NAV_BTN_HEIGHT
|
||||
|
||||
def _draw_current_panel(self, rect: rl.Rectangle):
|
||||
rl.draw_rectangle_rounded(
|
||||
rl.Rectangle(rect.x + 10, rect.y + 10, rect.width - 20, rect.height - 20), 0.04, 30, PANEL_COLOR
|
||||
)
|
||||
rl.draw_rectangle_rounded(rl.Rectangle(rect.x + 10, rect.y + 10, rect.width - 20, rect.height - 20), 0.04, 30, PANEL_COLOR)
|
||||
content_rect = rl.Rectangle(rect.x + PANEL_MARGIN, rect.y + 25, rect.width - (PANEL_MARGIN * 2), rect.height - 50)
|
||||
# rl.draw_rectangle_rounded(content_rect, 0.03, 30, PANEL_COLOR)
|
||||
panel = self._panels[self._current_panel]
|
||||
@@ -146,10 +178,9 @@ class SettingsLayout(Widget):
|
||||
panel.instance.render(content_rect)
|
||||
|
||||
def _handle_mouse_release(self, mouse_pos: MousePos) -> None:
|
||||
# Check close button
|
||||
if rl.check_collision_point_rec(mouse_pos, self._close_btn_rect):
|
||||
if self._close_callback:
|
||||
self._close_callback()
|
||||
# Check back/close button - hierarchical navigation
|
||||
if rl.check_collision_point_rec(mouse_pos, self._back_btn_rect):
|
||||
self._handle_back_navigation()
|
||||
return
|
||||
|
||||
# Check navigation buttons
|
||||
|
||||
@@ -7,7 +7,7 @@ from openpilot.system.ui.lib.application import gui_app
|
||||
from openpilot.system.ui.lib.multilang import tr, trn
|
||||
from openpilot.system.ui.widgets import Widget, DialogResult
|
||||
from openpilot.system.ui.widgets.confirm_dialog import ConfirmDialog
|
||||
from openpilot.system.ui.widgets.list_view import button_item, text_item, ListItem
|
||||
from openpilot.system.ui.widgets.list_view import button_item, text_item, toggle_item, ListItem
|
||||
from openpilot.system.ui.widgets.option_dialog import MultiOptionDialog
|
||||
from openpilot.system.ui.widgets.scroller_tici import Scroller
|
||||
|
||||
@@ -54,6 +54,12 @@ class SoftwareLayout(Widget):
|
||||
|
||||
self._onroad_label = ListItem(lambda: tr("Updates are only downloaded while the car is off."))
|
||||
self._version_item = text_item(lambda: tr("Current Version"), ui_state.params.get("UpdaterCurrentDescription") or "")
|
||||
self._auto_updates_toggle = toggle_item(
|
||||
lambda: tr("Automatically Install Updates"),
|
||||
lambda: tr("Automatically install updates when parked with an active internet connection."),
|
||||
initial_state=ui_state.params.get_bool("AutomaticUpdates"),
|
||||
callback=self._on_auto_updates_toggle,
|
||||
)
|
||||
self._download_btn = button_item(lambda: tr("Download"), lambda: tr("CHECK"), callback=self._on_download_update)
|
||||
|
||||
# Install button is initially hidden
|
||||
@@ -73,6 +79,7 @@ class SoftwareLayout(Widget):
|
||||
self._scroller = Scroller([
|
||||
self._onroad_label,
|
||||
self._version_item,
|
||||
self._auto_updates_toggle,
|
||||
self._download_btn,
|
||||
self._install_btn,
|
||||
self._branch_btn,
|
||||
@@ -94,6 +101,7 @@ class SoftwareLayout(Widget):
|
||||
current_release_notes = (ui_state.params.get("UpdaterCurrentReleaseNotes") or b"").decode("utf-8", "replace")
|
||||
self._version_item.action_item.set_text(current_desc)
|
||||
self._version_item.set_description(current_release_notes)
|
||||
self._auto_updates_toggle.action_item.set_state(ui_state.params.get_bool("AutomaticUpdates"))
|
||||
|
||||
# Update download button visibility and state
|
||||
self._download_btn.set_visible(ui_state.is_offroad())
|
||||
@@ -164,6 +172,9 @@ class SoftwareLayout(Widget):
|
||||
self._waiting_start_ts = time.monotonic()
|
||||
os.system("pkill -SIGHUP -f system.updated.updated")
|
||||
|
||||
def _on_auto_updates_toggle(self, enabled: bool):
|
||||
ui_state.params.put_bool("AutomaticUpdates", enabled)
|
||||
|
||||
def _on_uninstall(self):
|
||||
def handle_uninstall_confirmation(result):
|
||||
if result == DialogResult.CONFIRM:
|
||||
|
||||
@@ -0,0 +1,25 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from openpilot.system.ui.lib.multilang import tr, tr_noop
|
||||
from openpilot.system.ui.widgets.list_view import button_item
|
||||
from openpilot.system.ui.widgets.scroller_tici import Scroller
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.panel import StarPilotPanel
|
||||
|
||||
class StarPilotDataLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
items = [
|
||||
button_item(
|
||||
tr_noop("Manage Backups"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Create, restore, or delete backups</b> of your StarPilot settings."),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Manage Storage"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>View and manage storage usage</b> for models, maps, and other data."),
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
@@ -0,0 +1,25 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from openpilot.system.ui.lib.multilang import tr, tr_noop
|
||||
from openpilot.system.ui.widgets.list_view import button_item
|
||||
from openpilot.system.ui.widgets.scroller_tici import Scroller
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.panel import StarPilotPanel
|
||||
|
||||
class StarPilotDeviceLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
items = [
|
||||
button_item(
|
||||
tr_noop("Screen Controls"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Adjust screen brightness, timeout,</b> and other display settings."),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Device Settings"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Configure device-specific options</b> like orientation and controls."),
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
@@ -0,0 +1,429 @@
|
||||
from __future__ import annotations
|
||||
import json
|
||||
import os
|
||||
import threading
|
||||
from pathlib import Path
|
||||
|
||||
from openpilot.selfdrive.ui.ui_state import ui_state
|
||||
from openpilot.frogpilot.assets.model_manager import ModelManager
|
||||
from openpilot.system.hardware import HARDWARE, PC
|
||||
from openpilot.system.ui.lib.application import gui_app
|
||||
from openpilot.system.ui.lib.multilang import tr, tr_noop
|
||||
from openpilot.system.ui.widgets import DialogResult
|
||||
from openpilot.system.ui.widgets.confirm_dialog import ConfirmDialog, alert_dialog
|
||||
from openpilot.system.ui.widgets.selection_dialog import SelectionDialog
|
||||
from openpilot.system.ui.widgets.list_view import toggle_item, button_item
|
||||
from openpilot.system.ui.widgets.scroller_tici import Scroller
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.panel import StarPilotPanel
|
||||
|
||||
class StarPilotDrivingModelLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self._toggle_items = {}
|
||||
|
||||
if PC:
|
||||
self._model_dir = Path(os.path.expanduser("~/.comma/frogpilot/data/models"))
|
||||
else:
|
||||
self._model_dir = Path("/data/frogpilot/models")
|
||||
self._model_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
self._available_models = []
|
||||
self._available_model_names = []
|
||||
self._available_model_series = []
|
||||
self._available_model_versions = []
|
||||
self._model_released_dates = {}
|
||||
self._model_file_to_name = {}
|
||||
self._model_series_map = {}
|
||||
self._model_version_map = {}
|
||||
self._current_model_name = ""
|
||||
|
||||
self._toggle_items["ModelRandomizer"] = toggle_item(
|
||||
tr_noop("Model Randomizer"),
|
||||
tr_noop("<b>Driving models are chosen at random each drive</b> and feedback prompts are used to find the model that best suits your needs."),
|
||||
self._params.get_bool("ModelRandomizer"),
|
||||
callback=self._on_model_randomizer_toggled,
|
||||
)
|
||||
|
||||
self._toggle_items["AutomaticallyDownloadModels"] = toggle_item(
|
||||
tr_noop("Automatically Download New Models"),
|
||||
tr_noop("<b>Automatically download new driving models</b> as they become available."),
|
||||
self._params.get_bool("AutomaticallyDownloadModels"),
|
||||
callback=self._on_auto_download_toggled,
|
||||
)
|
||||
|
||||
self._select_model_btn = button_item(
|
||||
tr_noop("Select Driving Model"),
|
||||
lambda: tr("SELECT"),
|
||||
tr_noop("<b>Select the active driving model.</b>"),
|
||||
callback=self._on_select_model_clicked,
|
||||
)
|
||||
self._download_model_btn = button_item(
|
||||
tr_noop("Download Driving Models"),
|
||||
lambda: tr("DOWNLOAD"),
|
||||
tr_noop("<b>Download driving models to the device.</b>"),
|
||||
callback=self._on_download_clicked,
|
||||
)
|
||||
self._delete_model_btn = button_item(
|
||||
tr_noop("Delete Driving Models"),
|
||||
lambda: tr("DELETE"),
|
||||
tr_noop("<b>Delete driving models from the device.</b>"),
|
||||
callback=self._on_delete_clicked,
|
||||
)
|
||||
|
||||
items = [
|
||||
self._select_model_btn,
|
||||
self._download_model_btn,
|
||||
self._delete_model_btn,
|
||||
self._toggle_items["ModelRandomizer"],
|
||||
self._toggle_items["AutomaticallyDownloadModels"],
|
||||
button_item(
|
||||
tr_noop("Manage Model Blacklist"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Add or remove models</b> from the Model Randomizer's blacklist."),
|
||||
callback=self._on_blacklist_clicked,
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Manage Model Ratings"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Reset or view the saved ratings</b> for the driving models."),
|
||||
callback=self._on_scores_clicked,
|
||||
),
|
||||
]
|
||||
|
||||
self._model_manager = ModelManager(self._params, self._params_memory)
|
||||
self._download_thread = None
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
self._update_model_metadata()
|
||||
|
||||
def _render(self, rect: rl.Rectangle):
|
||||
self._update_state()
|
||||
super()._render(rect)
|
||||
|
||||
def show_event(self):
|
||||
super().show_event()
|
||||
self._update_model_metadata()
|
||||
|
||||
def refresh_visibility(self):
|
||||
current_level = int(self._params.get("TuningLevel", return_default=True, default="1") or "1")
|
||||
for key, item in self._toggle_items.items():
|
||||
min_level = self._tuning_levels.get(key, 0)
|
||||
item.set_visible(current_level >= min_level)
|
||||
|
||||
def _on_auto_download_toggled(self, state: bool):
|
||||
self._params.put_bool("AutomaticallyDownloadModels", state)
|
||||
|
||||
def _is_model_installed(self, key: str) -> bool:
|
||||
if not key:
|
||||
return False
|
||||
|
||||
has_thneed = False
|
||||
has_policy_meta = False
|
||||
has_policy_tg = False
|
||||
has_vision_meta = False
|
||||
has_vision_tg = False
|
||||
found_any = False
|
||||
|
||||
for file in self._model_dir.iterdir():
|
||||
if not (file.name.startswith(key) or file.name.startswith(key + "_")):
|
||||
continue
|
||||
|
||||
found_any = True
|
||||
ext = file.suffix.lower()
|
||||
base = file.stem
|
||||
|
||||
if ext == ".thneed":
|
||||
has_thneed = True
|
||||
elif ext == ".pkl":
|
||||
if "_driving_policy_metadata" in base:
|
||||
has_policy_meta = True
|
||||
elif "_driving_policy_tinygrad" in base:
|
||||
has_policy_tg = True
|
||||
elif "_driving_vision_metadata" in base:
|
||||
has_vision_meta = True
|
||||
elif "_driving_vision_tinygrad" in base:
|
||||
has_vision_tg = True
|
||||
|
||||
if has_thneed:
|
||||
return True
|
||||
|
||||
return has_policy_meta and has_policy_tg and has_vision_meta and has_vision_tg
|
||||
|
||||
def _update_model_metadata(self):
|
||||
available_models_raw = self._params.get("AvailableModels", encoding='utf-8')
|
||||
if not available_models_raw:
|
||||
manager = ModelManager(self._params, self._params_memory)
|
||||
manager.update_models()
|
||||
available_models_raw = self._params.get("AvailableModels", encoding='utf-8')
|
||||
|
||||
self._available_models = [m.strip() for m in (available_models_raw or "").split(",") if m.strip()]
|
||||
self._available_model_names = [m.strip() for m in (self._params.get("AvailableModelNames", encoding='utf-8') or "").split(",") if m.strip()]
|
||||
self._available_model_series = [m.strip() for m in (self._params.get("AvailableModelSeries", encoding='utf-8') or "").split(",") if m.strip()]
|
||||
self._available_model_versions = [m.strip() for m in (self._params.get("ModelVersions", encoding='utf-8') or "").split(",")]
|
||||
released_dates = (self._params.get("ModelReleasedDates", encoding='utf-8') or "").split(",")
|
||||
|
||||
self._model_file_to_name.clear()
|
||||
self._model_series_map.clear()
|
||||
self._model_version_map.clear()
|
||||
self._model_released_dates.clear()
|
||||
|
||||
size = min(len(self._available_models), len(self._available_model_names))
|
||||
for i in range(size):
|
||||
key = self._available_models[i].strip()
|
||||
name = self._available_model_names[i].strip()
|
||||
if not key or not name:
|
||||
continue
|
||||
|
||||
series = self._available_model_series[i].strip() if i < len(self._available_model_series) else tr("Custom Series")
|
||||
self._model_file_to_name[key] = name
|
||||
self._model_series_map[key] = series
|
||||
if i < len(self._available_model_versions):
|
||||
version = self._available_model_versions[i].strip()
|
||||
if version:
|
||||
self._model_version_map[key] = version
|
||||
if i < len(released_dates):
|
||||
date = released_dates[i].strip()
|
||||
if date:
|
||||
self._model_released_dates[key] = date
|
||||
|
||||
model_key = self._params.get("Model") or self._params.get("DrivingModel")
|
||||
if model_key:
|
||||
if isinstance(model_key, bytes):
|
||||
model_key = model_key.decode()
|
||||
if not model_key or not self._is_model_installed(model_key):
|
||||
model_key = self._params.get_default_value("Model") or self._params.get_default_value("DrivingModel") or ""
|
||||
if isinstance(model_key, bytes):
|
||||
model_key = model_key.decode()
|
||||
|
||||
self._current_model_name = self._model_file_to_name.get(model_key, "Default")
|
||||
self._select_model_btn.action_item._text_source = self._current_model_name
|
||||
|
||||
def _show_selection_dialog(self, title: str, options: dict[str, str] | list[str], current_val: str, on_confirm: Callable):
|
||||
if not options:
|
||||
gui_app.set_modal_overlay(alert_dialog(tr("No options available.")))
|
||||
return
|
||||
|
||||
if isinstance(options, list):
|
||||
def _on_close_list(res, val):
|
||||
if res == DialogResult.CONFIRM:
|
||||
on_confirm(val)
|
||||
dialog = SelectionDialog(title, options, current_val, on_close=_on_close_list)
|
||||
gui_app.set_modal_overlay(dialog)
|
||||
return
|
||||
|
||||
grouped = {}
|
||||
name_to_key = {}
|
||||
for key, name in options.items():
|
||||
series = self._model_series_map.get(key, tr("Custom Series"))
|
||||
if series not in grouped:
|
||||
grouped[series] = []
|
||||
grouped[series].append(name)
|
||||
name_to_key[name] = key
|
||||
|
||||
for series in grouped:
|
||||
grouped[series].sort()
|
||||
|
||||
sorted_series = sorted(grouped.keys())
|
||||
if "StarPilot" in sorted_series:
|
||||
sorted_series.remove("StarPilot")
|
||||
sorted_series.insert(0, "StarPilot")
|
||||
|
||||
final_grouped = {s: grouped[s] for s in sorted_series}
|
||||
|
||||
def _on_close_grouped(res, val):
|
||||
if res == DialogResult.CONFIRM:
|
||||
key = name_to_key.get(val, val)
|
||||
on_confirm(key)
|
||||
|
||||
def _on_favorite_toggled(key):
|
||||
favs = [f.strip() for f in (self._params.get("UserFavorites", encoding='utf-8') or "").split(",") if f.strip()]
|
||||
if key in favs:
|
||||
favs.remove(key)
|
||||
else:
|
||||
favs.append(key)
|
||||
self._params.put("UserFavorites", ",".join(favs))
|
||||
|
||||
user_favs = [f.strip() for f in (self._params.get("UserFavorites", encoding='utf-8') or "").split(",") if f.strip()]
|
||||
comm_favs = [f.strip() for f in (self._params.get("CommunityFavorites", encoding='utf-8') or "").split(",") if f.strip()]
|
||||
|
||||
dialog = SelectionDialog(
|
||||
title,
|
||||
final_grouped,
|
||||
current_val,
|
||||
on_close=_on_close_grouped,
|
||||
model_released_dates=self._model_released_dates,
|
||||
model_file_to_name=self._model_file_to_name,
|
||||
user_favorites=user_favs,
|
||||
community_favorites=comm_favs,
|
||||
on_favorite_toggled=_on_favorite_toggled
|
||||
)
|
||||
gui_app.set_modal_overlay(dialog)
|
||||
|
||||
def _on_select_model_clicked(self):
|
||||
installed_models = {k: v for k, v in self._model_file_to_name.items() if self._is_model_installed(k)}
|
||||
if not installed_models:
|
||||
return
|
||||
|
||||
def _on_confirm(model_key):
|
||||
self._params.put("Model", model_key)
|
||||
self._params.put("DrivingModel", model_key)
|
||||
self._params.put("DrivingModelName", installed_models[model_key])
|
||||
model_version = self._model_version_map.get(model_key, "")
|
||||
if model_version:
|
||||
self._params.put("ModelVersion", model_version)
|
||||
self._params.put("DrivingModelVersion", model_version)
|
||||
self._update_model_metadata()
|
||||
|
||||
if ui_state.started:
|
||||
reboot_dialog = ConfirmDialog(
|
||||
tr("Reboot required to take effect. Reboot now?"),
|
||||
tr("Reboot"),
|
||||
tr("Cancel"),
|
||||
on_close=lambda res: HARDWARE.reboot() if res == DialogResult.CONFIRM else None
|
||||
)
|
||||
gui_app.set_modal_overlay(reboot_dialog)
|
||||
|
||||
self._show_selection_dialog(tr("Select Driving Model"), installed_models, self._current_model_name, _on_confirm)
|
||||
|
||||
def _on_download_clicked(self):
|
||||
is_downloading = self._params_memory.get("ModelToDownload") or self._params_memory.get_bool("DownloadAllModels")
|
||||
if is_downloading:
|
||||
self._params_memory.remove("ModelToDownload")
|
||||
self._params_memory.put_bool("DownloadAllModels", False)
|
||||
self._params_memory.remove("ModelDownloadProgress")
|
||||
return
|
||||
|
||||
not_installed = {k: v for k, v in self._model_file_to_name.items() if not self._is_model_installed(k)}
|
||||
def _on_confirm(model_key):
|
||||
self._params_memory.put("ModelToDownload", model_key)
|
||||
self._params_memory.put("ModelDownloadProgress", "Downloading...")
|
||||
|
||||
self._show_selection_dialog(tr("Select Model to Download"), not_installed, "", _on_confirm)
|
||||
|
||||
def _on_delete_clicked(self):
|
||||
installed = {k: v for k, v in self._model_file_to_name.items() if self._is_model_installed(k)}
|
||||
default_key = self._params.get_default_value("Model") or ""
|
||||
if isinstance(default_key, bytes):
|
||||
default_key = default_key.decode()
|
||||
current_key = self._params.get("Model", encoding='utf-8') or ""
|
||||
deletable = {k: v for k, v in installed.items() if k != default_key and k != current_key}
|
||||
|
||||
def _on_confirm(model_key):
|
||||
def _execute_delete(confirm_res):
|
||||
if confirm_res == DialogResult.CONFIRM:
|
||||
for file in self._model_dir.iterdir():
|
||||
if file.name.startswith(model_key):
|
||||
file.unlink()
|
||||
self._update_model_metadata()
|
||||
|
||||
confirm = ConfirmDialog(
|
||||
tr(f"Are you sure you want to delete the '{deletable[model_key]}' model?"),
|
||||
tr("Delete"),
|
||||
on_close=_execute_delete
|
||||
)
|
||||
gui_app.set_modal_overlay(confirm)
|
||||
|
||||
self._show_selection_dialog(tr("Select Model to Delete"), deletable, "", _on_confirm)
|
||||
|
||||
def _on_blacklist_clicked(self):
|
||||
blacklisted = [m.strip() for m in (self._params.get("BlacklistedModels", encoding='utf-8') or "").split(",") if m.strip()]
|
||||
blacklisted = [b for b in blacklisted if b]
|
||||
|
||||
def _on_action_selected(res, val):
|
||||
if res == DialogResult.CONFIRM:
|
||||
if val == tr("ADD"):
|
||||
blacklistable = {k: v for k, v in self._model_file_to_name.items() if k not in blacklisted}
|
||||
self._show_selection_dialog(tr("Add to Blacklist"), blacklistable, "", lambda k: self._params.put("BlacklistedModels", ",".join(blacklisted + [k])))
|
||||
elif val == tr("REMOVE"):
|
||||
options = {k: self._model_file_to_name.get(k, k) for k in blacklisted}
|
||||
def _remove(k):
|
||||
blacklisted.remove(k)
|
||||
self._params.put("BlacklistedModels", ",".join(blacklisted))
|
||||
self._show_selection_dialog(tr("Remove from Blacklist"), options, "", _remove)
|
||||
elif val == tr("RESET ALL"):
|
||||
self._params.remove("BlacklistedModels")
|
||||
|
||||
dialog = SelectionDialog(
|
||||
tr("Manage Blacklist"),
|
||||
[tr("ADD"), tr("REMOVE"), tr("RESET ALL")],
|
||||
on_close=_on_action_selected
|
||||
)
|
||||
gui_app.set_modal_overlay(dialog)
|
||||
|
||||
def _on_scores_clicked(self):
|
||||
scores_raw = self._params.get("ModelDrivesAndScores", encoding='utf-8') or ""
|
||||
if not scores_raw:
|
||||
gui_app.set_modal_overlay(alert_dialog(tr("No model ratings found.")))
|
||||
return
|
||||
|
||||
try:
|
||||
scores = json.loads(scores_raw)
|
||||
lines = [f"{k}: {v.get('Score', 0)}% ({v.get('Drives', 0)} drives)" for k, v in scores.items()]
|
||||
confirm = ConfirmDialog("\n".join(lines), tr("Close"), rich=True)
|
||||
gui_app.set_modal_overlay(confirm)
|
||||
except:
|
||||
pass
|
||||
|
||||
def _on_model_randomizer_toggled(self, state: bool):
|
||||
self._params.put_bool("ModelRandomizer", state)
|
||||
if state:
|
||||
not_installed = [k for k in self._model_file_to_name if not self._is_model_installed(k)]
|
||||
if not_installed:
|
||||
def _on_download_confirm(res):
|
||||
if res == DialogResult.CONFIRM:
|
||||
self._params_memory.put_bool("DownloadAllModels", True)
|
||||
self._params_memory.put("ModelDownloadProgress", "Downloading...")
|
||||
|
||||
confirm = ConfirmDialog(
|
||||
tr("Model Randomizer works best with all models. Download all now?"),
|
||||
tr("Download All"),
|
||||
on_close=_on_download_confirm
|
||||
)
|
||||
gui_app.set_modal_overlay(confirm)
|
||||
|
||||
def _update_state(self):
|
||||
if not self.is_visible:
|
||||
return
|
||||
|
||||
model_to_download = self._params_memory.get("ModelToDownload", encoding='utf-8') or ""
|
||||
download_all = self._params_memory.get_bool("DownloadAllModels")
|
||||
progress = self._params_memory.get("ModelDownloadProgress", encoding='utf-8') or ""
|
||||
is_downloading = bool(model_to_download or download_all)
|
||||
|
||||
if is_downloading and (self._download_thread is None or not self._download_thread.is_alive()):
|
||||
def _download_task():
|
||||
try:
|
||||
if download_all:
|
||||
print("Starting [All Models] download thread...")
|
||||
self._model_manager.download_all_models()
|
||||
else:
|
||||
print(f"Starting [{model_to_download}] download thread...")
|
||||
self._model_manager.download_model(model_to_download)
|
||||
print("Download thread finished successfully.")
|
||||
except Exception as e:
|
||||
print(f"Download thread CRASHED: {e}")
|
||||
import traceback
|
||||
traceback.print_exc()
|
||||
finally:
|
||||
self._download_thread = None
|
||||
|
||||
self._download_thread = threading.Thread(target=_download_task, daemon=True)
|
||||
self._download_thread.start()
|
||||
|
||||
if is_downloading:
|
||||
self._download_model_btn.action_item._text_source = tr("CANCEL")
|
||||
self._download_model_btn.action_item._value_source = progress if progress else tr("Downloading...")
|
||||
else:
|
||||
self._download_model_btn.action_item._text_source = tr("DOWNLOAD")
|
||||
parked = not ui_state.started
|
||||
online = ui_state.sm["deviceState"].networkType != 0 if ui_state.sm.valid.get("deviceState", False) else True
|
||||
if not online:
|
||||
self._download_model_btn.action_item._value_source = tr("Offline...")
|
||||
elif not parked:
|
||||
self._download_model_btn.action_item._value_source = tr("Not parked")
|
||||
else:
|
||||
self._download_model_btn.action_item._value_source = ""
|
||||
|
||||
all_installed = all(self._is_model_installed(k) for k in self._model_file_to_name)
|
||||
if all_installed:
|
||||
self._download_model_btn.action_item._value_source = tr("All Downloaded!")
|
||||
@@ -0,0 +1,380 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from openpilot.selfdrive.ui.lib.starpilot_state import starpilot_state
|
||||
from openpilot.system.ui.lib.multilang import tr, tr_noop
|
||||
from openpilot.system.ui.widgets import DialogResult
|
||||
from openpilot.system.ui.widgets.confirm_dialog import ConfirmDialog
|
||||
from openpilot.system.ui.widgets.list_view import button_item, value_button_item, button_toggle_item, toggle_item, value_item
|
||||
from openpilot.system.ui.widgets.scroller_tici import Scroller
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.panel import StarPilotPanel
|
||||
|
||||
class StarPilotAdvancedLateralLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
items = [
|
||||
value_button_item(
|
||||
lambda: (
|
||||
tr("Actuator Delay")
|
||||
+ (f" (Default: {starpilot_state.car_state.steerActuatorDelay:.2f})" if starpilot_state.car_state.steerActuatorDelay != 0 else "")
|
||||
),
|
||||
"SteerDelay",
|
||||
min_val=0.01,
|
||||
max_val=1.0,
|
||||
step=0.01,
|
||||
button_text="Reset",
|
||||
button_callback=lambda: self._params.put_float("SteerDelay", starpilot_state.car_state.steerActuatorDelay),
|
||||
description=tr_noop(
|
||||
"<b>The time between openpilot's steering command and the vehicle's response.</b> Increase if the vehicle reacts late; decrease if it feels jumpy. Auto-learned by default."
|
||||
),
|
||||
enabled=lambda: starpilot_state.car_state.steerActuatorDelay != 0,
|
||||
),
|
||||
value_button_item(
|
||||
lambda: tr("Friction") + (f" (Default: {starpilot_state.car_state.friction:.2f})" if starpilot_state.car_state.friction != 0 else ""),
|
||||
"SteerFriction",
|
||||
min_val=0.0,
|
||||
max_val=1.0,
|
||||
step=0.01,
|
||||
button_text="Reset",
|
||||
button_callback=lambda: self._params.put_float("SteerFriction", starpilot_state.car_state.friction),
|
||||
description=tr_noop(
|
||||
"<b>Compensates for steering friction.</b> Increase if the wheel sticks near center; decrease if it jitters. Auto-learned by default."
|
||||
),
|
||||
enabled=lambda: (
|
||||
starpilot_state.car_state.friction != 0
|
||||
and (not starpilot_state.car_state.hasAutoTune or (starpilot_state.car_state.hasAutoTune and self._params.get_bool("ForceAutoTuneOff")))
|
||||
),
|
||||
),
|
||||
value_button_item(
|
||||
lambda: tr("Kp Factor") + (f" (Default: {starpilot_state.car_state.steerKp:.2f})" if starpilot_state.car_state.steerKp != 0 else ""),
|
||||
"SteerKP",
|
||||
min_val=lambda: starpilot_state.car_state.steerKp * 0.5,
|
||||
max_val=lambda: starpilot_state.car_state.steerKp * 1.5,
|
||||
step=0.01,
|
||||
button_text="Reset",
|
||||
button_callback=lambda: self._params.put_float("SteerKP", starpilot_state.car_state.steerKp),
|
||||
description=tr_noop(
|
||||
"<b>How strongly openpilot corrects lane position.</b> Higher is tighter but twitchier; lower is smoother but slower. Auto-learned by default."
|
||||
),
|
||||
enabled=lambda: starpilot_state.car_state.steerKp != 0 and not starpilot_state.car_state.isAngleCar,
|
||||
),
|
||||
value_button_item(
|
||||
lambda: (
|
||||
tr("Lateral Acceleration") + (f" (Default: {starpilot_state.car_state.latAccelFactor:.2f})" if starpilot_state.car_state.latAccelFactor != 0 else "")
|
||||
),
|
||||
"SteerLatAccel",
|
||||
min_val=lambda: starpilot_state.car_state.latAccelFactor * 0.5,
|
||||
max_val=lambda: starpilot_state.car_state.latAccelFactor * 1.5,
|
||||
step=0.01,
|
||||
button_text="Reset",
|
||||
button_callback=lambda: self._params.put_float("SteerLatAccel", starpilot_state.car_state.latAccelFactor),
|
||||
description=tr_noop(
|
||||
"<b>Maps steering torque to turning response.</b> Increase for sharper turns; decrease for gentler steering. Auto-learned by default."
|
||||
),
|
||||
enabled=lambda: (
|
||||
starpilot_state.car_state.latAccelFactor != 0
|
||||
and (not starpilot_state.car_state.hasAutoTune or (starpilot_state.car_state.hasAutoTune and self._params.get_bool("ForceAutoTuneOff")))
|
||||
),
|
||||
),
|
||||
value_button_item(
|
||||
lambda: tr("Steer Ratio") + (f" (Default: {starpilot_state.car_state.steerRatio:.2f})" if starpilot_state.car_state.steerRatio != 0 else ""),
|
||||
"SteerRatio",
|
||||
min_val=lambda: starpilot_state.car_state.steerRatio * 0.5,
|
||||
max_val=lambda: starpilot_state.car_state.steerRatio * 1.5,
|
||||
step=0.01,
|
||||
button_text="Reset",
|
||||
button_callback=lambda: self._params.put_float("SteerRatio", starpilot_state.car_state.steerRatio),
|
||||
description=tr_noop(
|
||||
"<b>The relationship between steering wheel rotation and road wheel angle.</b> Increase if steering feels too quick or twitchy; decrease if it feels too slow or weak. Auto-learned by default."
|
||||
),
|
||||
enabled=lambda: (
|
||||
starpilot_state.car_state.steerRatio != 0
|
||||
and (not starpilot_state.car_state.hasAutoTune or (starpilot_state.car_state.hasAutoTune and self._params.get_bool("ForceAutoTuneOff")))
|
||||
),
|
||||
),
|
||||
toggle_item(
|
||||
tr_noop("Force Auto-Tune On"),
|
||||
tr_noop("<b>Force-enable openpilot's live auto-tuning for \"Friction\" and \"Lateral Acceleration\".</b>"),
|
||||
self._params.get_bool("ForceAutoTune"),
|
||||
callback=lambda x: self._params.put_bool("ForceAutoTune", x),
|
||||
enabled=lambda: not starpilot_state.car_state.hasAutoTune and not starpilot_state.car_state.isAngleCar,
|
||||
),
|
||||
toggle_item(
|
||||
tr_noop("Force Auto-Tune Off"),
|
||||
tr_noop("<b>Force-disable openpilot's live auto-tuning for \"Friction\" and \"Lateral Acceleration\" and use the set value instead.</b>"),
|
||||
self._params.get_bool("ForceAutoTuneOff"),
|
||||
callback=lambda x: self._params.put_bool("ForceAutoTuneOff", x),
|
||||
enabled=lambda: starpilot_state.car_state.hasAutoTune,
|
||||
),
|
||||
toggle_item(
|
||||
tr_noop("Force Torque Controller"),
|
||||
tr_noop("<b>Use torque-based steering control instead of angle-based control for smoother lane keeping, especially in curves.</b>"),
|
||||
self._params.get_bool("ForceTorqueController"),
|
||||
callback=lambda x: self._on_reboot_toggle("ForceTorqueController", x),
|
||||
enabled=lambda: not starpilot_state.car_state.isAngleCar and not starpilot_state.car_state.isTorqueCar,
|
||||
),
|
||||
]
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
|
||||
def _on_reboot_toggle(self, key, state):
|
||||
self._params.put_bool(key, state)
|
||||
from openpilot.selfdrive.ui.ui_state import ui_state
|
||||
|
||||
if ui_state.started:
|
||||
from openpilot.system.ui.lib.application import gui_app
|
||||
|
||||
def _confirm_reboot(res):
|
||||
gui_app.set_modal_overlay(None)
|
||||
if res == DialogResult.CONFIRM:
|
||||
from openpilot.system.hardware import HARDWARE
|
||||
HARDWARE.reboot()
|
||||
|
||||
dialog = ConfirmDialog("Reboot required to take effect. Reboot now?", "Reboot", "Cancel", on_close=_confirm_reboot)
|
||||
gui_app.set_modal_overlay(dialog)
|
||||
|
||||
class StarPilotAlwaysOnLateralLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
items = [
|
||||
toggle_item(
|
||||
tr_noop("Always On Lateral"),
|
||||
tr_noop("<b>openpilot's steering remains active even when the accelerator or brake pedals are pressed.</b>"),
|
||||
self._params.get_bool("AlwaysOnLateral"),
|
||||
callback=lambda x: self._on_reboot_toggle("AlwaysOnLateral", x),
|
||||
icon="toggle_icons/icon_always_on_lateral.png",
|
||||
starpilot_icon=True,
|
||||
),
|
||||
toggle_item(
|
||||
tr_noop("Enable With LKAS"),
|
||||
tr_noop("<b>Enable \"Always On Lateral\" whenever \"LKAS\" is on, even when openpilot is not engaged.</b>"),
|
||||
self._params.get_bool("AlwaysOnLateralLKAS"),
|
||||
callback=lambda x: self._params.put_bool("AlwaysOnLateralLKAS", x),
|
||||
enabled=lambda: starpilot_state.car_state.lkasAllowedForAOL,
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Pause on Brake Press Below"),
|
||||
"PauseAOLOnBrake",
|
||||
min_val=0,
|
||||
max_val=99,
|
||||
step=1,
|
||||
unit="mph",
|
||||
description=tr_noop("<b>Pause \"Always On Lateral\" below the set speed while the brake pedal is pressed.</b>"),
|
||||
is_metric=True,
|
||||
),
|
||||
]
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
|
||||
def _on_reboot_toggle(self, key, state):
|
||||
self._params.put_bool(key, state)
|
||||
from openpilot.selfdrive.ui.ui_state import ui_state
|
||||
|
||||
if ui_state.started:
|
||||
from openpilot.system.ui.lib.application import gui_app
|
||||
|
||||
def _confirm_reboot(res):
|
||||
gui_app.set_modal_overlay(None)
|
||||
if res == DialogResult.CONFIRM:
|
||||
from openpilot.system.hardware import HARDWARE
|
||||
HARDWARE.reboot()
|
||||
|
||||
dialog = ConfirmDialog("Reboot required to take effect. Reboot now?", "Reboot", "Cancel", on_close=_confirm_reboot)
|
||||
gui_app.set_modal_overlay(dialog)
|
||||
|
||||
class StarPilotLaneChangesLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
def _get_lane_change_labels():
|
||||
labels = {0.0: tr("Instant")}
|
||||
for i in range(1, 51):
|
||||
val = i / 10.0
|
||||
labels[val] = f"{val:.1f} seconds" if val != 1.0 else "1.0 second"
|
||||
return labels
|
||||
|
||||
items = [
|
||||
toggle_item(
|
||||
tr_noop("Lane Changes"),
|
||||
tr_noop("<b>Allow openpilot to change lanes.</b>"),
|
||||
self._params.get_bool("LaneChanges"),
|
||||
callback=lambda x: self._params.put_bool("LaneChanges", x),
|
||||
icon="toggle_icons/icon_lane.png",
|
||||
starpilot_icon=True,
|
||||
),
|
||||
toggle_item(
|
||||
tr_noop("Automatic Lane Changes"),
|
||||
tr_noop("<b>When the turn signal is on, openpilot will automatically change lanes.</b> No steering-wheel nudge required!"),
|
||||
self._params.get_bool("NudgelessLaneChange"),
|
||||
callback=lambda x: self._params.put_bool("NudgelessLaneChange", x),
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Lane Change Delay"),
|
||||
"LaneChangeTime",
|
||||
min_val=0.0,
|
||||
max_val=5.0,
|
||||
step=0.1,
|
||||
description=tr_noop("<b>Delay between turn signal activation and the start of an automatic lane change.</b>"),
|
||||
labels=_get_lane_change_labels(),
|
||||
enabled=lambda: self._params.get_bool("LaneChanges") and self._params.get_bool("NudgelessLaneChange"),
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Minimum Lane Change Speed"),
|
||||
"MinimumLaneChangeSpeed",
|
||||
min_val=0,
|
||||
max_val=99,
|
||||
step=1,
|
||||
unit="mph",
|
||||
description=tr_noop("<b>Lowest speed at which openpilot will change lanes.</b>"),
|
||||
is_metric=True,
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Minimum Lane Width"),
|
||||
"LaneDetectionWidth",
|
||||
min_val=0.0,
|
||||
max_val=15.0,
|
||||
step=0.1,
|
||||
unit="feet",
|
||||
description=tr_noop("<b>Prevent automatic lane changes into lanes narrower than the set width.</b>"),
|
||||
enabled=lambda: self._params.get_bool("LaneChanges") and self._params.get_bool("NudgelessLaneChange"),
|
||||
is_metric=True,
|
||||
),
|
||||
toggle_item(
|
||||
tr_noop("One Lane Change Per Signal"),
|
||||
tr_noop("<b>Limit automatic lane changes to one per turn-signal activation.</b>"),
|
||||
self._params.get_bool("OneLaneChange"),
|
||||
callback=lambda x: self._params.put_bool("OneLaneChange", x),
|
||||
),
|
||||
]
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
|
||||
class StarPilotLateralTuneLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
items = [
|
||||
toggle_item(
|
||||
tr_noop("Force Turn Desires Below Lane Change Speed"),
|
||||
tr_noop("<b>While driving below the minimum lane change speed with an active turn signal, instruct openpilot to turn left/right.</b>"),
|
||||
self._params.get_bool("TurnDesires"),
|
||||
callback=lambda x: self._params.put_bool("TurnDesires", x),
|
||||
),
|
||||
toggle_item(
|
||||
tr_noop("Neural Network Feedforward (NNFF)"),
|
||||
tr_noop(
|
||||
"<b>Twilsonco's \"Neural Network FeedForward\" controller.</b> Uses a trained neural network model to predict steering torque based on vehicle speed, roll, and past/future planned path data for smoother, model-based steering."
|
||||
),
|
||||
self._params.get_bool("NNFF"),
|
||||
callback=lambda x: self._on_reboot_toggle("NNFF", x),
|
||||
enabled=lambda: starpilot_state.car_state.hasNNFFLog and not starpilot_state.car_state.isAngleCar,
|
||||
),
|
||||
toggle_item(
|
||||
tr_noop("Neural Network Feedforward (NNFF) Lite"),
|
||||
tr_noop(
|
||||
"<b>A lightweight version of Twilsonco's \"Neural Network FeedForward\" controller.</b> Uses the \"look-ahead\" planned lateral jerk logic from the full model to help smoothen steering adjustments in curves, but does not use the full neural network for torque calculation."
|
||||
),
|
||||
self._params.get_bool("NNFFLite"),
|
||||
callback=lambda x: self._on_reboot_toggle("NNFFLite", x),
|
||||
enabled=lambda: not self._params.get_bool("NNFF") and not starpilot_state.car_state.isAngleCar,
|
||||
),
|
||||
]
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
|
||||
def _on_reboot_toggle(self, key, state):
|
||||
self._params.put_bool(key, state)
|
||||
from openpilot.selfdrive.ui.ui_state import ui_state
|
||||
|
||||
if ui_state.started:
|
||||
from openpilot.system.ui.lib.application import gui_app
|
||||
|
||||
def _confirm_reboot(res):
|
||||
gui_app.set_modal_overlay(None)
|
||||
if res == DialogResult.CONFIRM:
|
||||
from openpilot.system.hardware import HARDWARE
|
||||
HARDWARE.reboot()
|
||||
|
||||
dialog = ConfirmDialog("Reboot required to take effect. Reboot now?", "Reboot", "Cancel", on_close=_confirm_reboot)
|
||||
gui_app.set_modal_overlay(dialog)
|
||||
|
||||
class StarPilotLateralQOLLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
items = [
|
||||
value_button_item(
|
||||
tr_noop("Pause Steering Below"),
|
||||
"PauseLateralSpeed",
|
||||
min_val=0,
|
||||
max_val=99,
|
||||
step=1,
|
||||
unit="mph",
|
||||
description=tr_noop("<b>Pause steering below the set speed.</b>"),
|
||||
sub_toggles=[("PauseLateralOnSignal", True)],
|
||||
labels={0: tr_noop("Off")},
|
||||
is_metric=True,
|
||||
)
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
|
||||
class StarPilotLateralLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
self._sub_panels = {
|
||||
"advanced_lateral": StarPilotAdvancedLateralLayout(),
|
||||
"always_on_lateral": StarPilotAlwaysOnLateralLayout(),
|
||||
"lane_changes": StarPilotLaneChangesLayout(),
|
||||
"lateral_tune": StarPilotLateralTuneLayout(),
|
||||
"qol": StarPilotLateralQOLLayout(),
|
||||
}
|
||||
|
||||
for name, panel in self._sub_panels.items():
|
||||
if hasattr(panel, 'set_navigate_callback'):
|
||||
panel.set_navigate_callback(self._navigate_to)
|
||||
if hasattr(panel, 'set_back_callback'):
|
||||
panel.set_back_callback(self._go_back)
|
||||
|
||||
items = [
|
||||
button_item(
|
||||
tr_noop("Advanced Lateral Tuning"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Advanced steering control changes to fine-tune how openpilot drives.</b>"),
|
||||
callback=lambda: self._navigate_to("advanced_lateral"),
|
||||
icon="toggle_icons/icon_advanced_lateral_tune.png",
|
||||
starpilot_icon=True,
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Always On Lateral"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>openpilot's steering remains active even when the accelerator or brake pedals are pressed.</b>"),
|
||||
callback=lambda: self._navigate_to("always_on_lateral"),
|
||||
icon="toggle_icons/icon_always_on_lateral.png",
|
||||
starpilot_icon=True,
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Lane Changes"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Allow openpilot to change lanes.</b>"),
|
||||
callback=lambda: self._navigate_to("lane_changes"),
|
||||
icon="toggle_icons/icon_lane.png",
|
||||
starpilot_icon=True,
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Lateral Tuning"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Miscellaneous steering control changes</b> to fine-tune how openpilot drives."),
|
||||
callback=lambda: self._navigate_to("lateral_tune"),
|
||||
icon="toggle_icons/icon_lateral_tune.png",
|
||||
starpilot_icon=True,
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Quality of Life"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Steering control changes to fine-tune how openpilot drives.</b>"),
|
||||
callback=lambda: self._navigate_to("qol"),
|
||||
icon="toggle_icons/icon_quality_of_life.png",
|
||||
starpilot_icon=True,
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
@@ -0,0 +1,368 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from openpilot.system.ui.lib.multilang import tr, tr_noop
|
||||
from openpilot.system.ui.widgets.list_view import button_item, value_item
|
||||
from openpilot.system.ui.widgets.scroller_tici import Scroller
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.panel import StarPilotPanel
|
||||
|
||||
class StarPilotLongitudinalLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
# Main panel items
|
||||
items = [
|
||||
button_item(
|
||||
tr_noop("Advanced Longitudinal Tuning"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Advanced acceleration and braking control changes</b> to fine-tune how openpilot drives."),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Conditional Experimental Mode"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Automatically switch to Experimental Mode</b> when set conditions are met."),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Curve Speed Controller"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Automatically slow down for upcoming curves</b> using data learned from your driving style."),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Driving Personalities"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Customize the Driving Personalities</b> to better match your driving style."),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Longitudinal Tuning"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Acceleration and braking control changes</b> to fine-tune how openpilot drives."),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Quality of Life"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Miscellaneous acceleration and braking control changes</b> to fine-tune how openpilot drives."),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Weather"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Adjust driving behavior</b> based on weather conditions."),
|
||||
callback=lambda: self._navigate_to("weather"),
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
|
||||
# Sub-panels
|
||||
self._sub_panels = {
|
||||
"weather": StarPilotWeatherLayout(),
|
||||
"low_visibility": StarPilotLowVisibilityLayout(),
|
||||
"rain": StarPilotRainLayout(),
|
||||
"rainstorm": StarPilotRainStormLayout(),
|
||||
"snow": StarPilotSnowLayout(),
|
||||
}
|
||||
|
||||
# Wire up navigation callbacks for sub-panels
|
||||
for name, panel in self._sub_panels.items():
|
||||
if hasattr(panel, 'set_navigate_callback'):
|
||||
panel.set_navigate_callback(self._navigate_to)
|
||||
if hasattr(panel, 'set_back_callback'):
|
||||
panel.set_back_callback(self._go_back)
|
||||
|
||||
class StarPilotWeatherLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
items = [
|
||||
button_item(
|
||||
tr_noop("Low Visibility"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Driving adjustments for fog, haze, or other low-visibility conditions.</b>"),
|
||||
callback=lambda: self._navigate("low_visibility"),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Rain"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Driving adjustments for rainy conditions.</b>"),
|
||||
callback=lambda: self._navigate("rain"),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Rainstorms"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Driving adjustments for rainstorms.</b>"),
|
||||
callback=lambda: self._navigate("rainstorm"),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Snow"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Driving adjustments for snowy conditions.</b>"),
|
||||
callback=lambda: self._navigate("snow"),
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
|
||||
def _navigate(self, sub_panel: str):
|
||||
if self._navigate_callback:
|
||||
self._navigate_callback(sub_panel)
|
||||
|
||||
class StarPilotLowVisibilityLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
def save_following(value: float):
|
||||
self._params.put_int("IncreaseFollowingLowVisibility", int(value))
|
||||
|
||||
def save_stopped_distance(value: float):
|
||||
self._params.put_int("IncreasedStoppedDistanceLowVisibility", int(value))
|
||||
|
||||
def save_reduce_accel(value: float):
|
||||
self._params.put_int("ReduceAccelerationLowVisibility", int(value))
|
||||
|
||||
def save_reduce_lateral(value: float):
|
||||
self._params.put_int("ReduceLateralAccelerationLowVisibility", int(value))
|
||||
|
||||
items = [
|
||||
value_item(
|
||||
tr_noop("Increase Following Distance by:"),
|
||||
lambda: self._params.get_int("IncreaseFollowingLowVisibility", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=3,
|
||||
step=0.5,
|
||||
unit=" seconds",
|
||||
description=tr_noop("<b>Add extra space behind lead vehicles in low visibility.</b> Increase for more space; decrease for tighter gaps."),
|
||||
callback=save_following,
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Increase Stopped Distance by:"),
|
||||
lambda: self._params.get_int("IncreasedStoppedDistanceLowVisibility", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=10,
|
||||
step=1,
|
||||
unit=" feet",
|
||||
description=tr_noop("<b>Add extra buffer when stopped behind vehicles in low visibility.</b> Increase for more room; decrease for shorter gaps."),
|
||||
callback=save_stopped_distance,
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Reduce Acceleration by:"),
|
||||
lambda: self._params.get_int("ReduceAccelerationLowVisibility", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=50,
|
||||
step=5,
|
||||
unit="%",
|
||||
description=tr_noop(
|
||||
"<b>Lower the maximum acceleration in low visibility.</b> Increase for softer takeoffs; decrease for quicker but less stable takeoffs."
|
||||
),
|
||||
callback=save_reduce_accel,
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Reduce Speed in Curves by:"),
|
||||
lambda: self._params.get_int("ReduceLateralAccelerationLowVisibility", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=50,
|
||||
step=5,
|
||||
unit="%",
|
||||
description=tr_noop(
|
||||
"<b>Lower the desired speed while driving through curves in low visibility.</b> Increase for safer, gentler turns; decrease for more aggressive driving in curves."
|
||||
),
|
||||
callback=save_reduce_lateral,
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
|
||||
class StarPilotRainLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
def save_following(value: float):
|
||||
self._params.put_int("IncreaseFollowingRain", int(value))
|
||||
|
||||
def save_stopped_distance(value: float):
|
||||
self._params.put_int("IncreasedStoppedDistanceRain", int(value))
|
||||
|
||||
def save_reduce_accel(value: float):
|
||||
self._params.put_int("ReduceAccelerationRain", int(value))
|
||||
|
||||
def save_reduce_lateral(value: float):
|
||||
self._params.put_int("ReduceLateralAccelerationRain", int(value))
|
||||
|
||||
items = [
|
||||
value_item(
|
||||
tr_noop("Increase Following Distance by:"),
|
||||
lambda: self._params.get_int("IncreaseFollowingRain", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=3,
|
||||
step=0.5,
|
||||
unit=" seconds",
|
||||
description=tr_noop("<b>Add extra space behind lead vehicles in rain.</b> Increase for more space; decrease for tighter gaps."),
|
||||
callback=save_following,
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Increase Stopped Distance by:"),
|
||||
lambda: self._params.get_int("IncreasedStoppedDistanceRain", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=10,
|
||||
step=1,
|
||||
unit=" feet",
|
||||
description=tr_noop("<b>Add extra buffer when stopped behind vehicles in rain.</b> Increase for more room; decrease for shorter gaps."),
|
||||
callback=save_stopped_distance,
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Reduce Acceleration by:"),
|
||||
lambda: self._params.get_int("ReduceAccelerationRain", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=50,
|
||||
step=5,
|
||||
unit="%",
|
||||
description=tr_noop("<b>Lower the maximum acceleration in rain.</b> Increase for softer takeoffs; decrease for quicker but less stable takeoffs."),
|
||||
callback=save_reduce_accel,
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Reduce Speed in Curves by:"),
|
||||
lambda: self._params.get_int("ReduceLateralAccelerationRain", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=50,
|
||||
step=5,
|
||||
unit="%",
|
||||
description=tr_noop(
|
||||
"<b>Lower the desired speed while driving through curves in rain.</b> Increase for safer, gentler turns; decrease for more aggressive driving in curves."
|
||||
),
|
||||
callback=save_reduce_lateral,
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
|
||||
class StarPilotRainStormLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
def save_following(value: float):
|
||||
self._params.put_int("IncreaseFollowingRainStorm", int(value))
|
||||
|
||||
def save_stopped_distance(value: float):
|
||||
self._params.put_int("IncreasedStoppedDistanceRainStorm", int(value))
|
||||
|
||||
def save_reduce_accel(value: float):
|
||||
self._params.put_int("ReduceAccelerationRainStorm", int(value))
|
||||
|
||||
def save_reduce_lateral(value: float):
|
||||
self._params.put_int("ReduceLateralAccelerationRainStorm", int(value))
|
||||
|
||||
items = [
|
||||
value_item(
|
||||
tr_noop("Increase Following Distance by:"),
|
||||
lambda: self._params.get_int("IncreaseFollowingRainStorm", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=3,
|
||||
step=0.5,
|
||||
unit=" seconds",
|
||||
description=tr_noop("<b>Add extra space behind lead vehicles in a rainstorm.</b> Increase for more space; decrease for tighter gaps."),
|
||||
callback=save_following,
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Increase Stopped Distance by:"),
|
||||
lambda: self._params.get_int("IncreasedStoppedDistanceRainStorm", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=10,
|
||||
step=1,
|
||||
unit=" feet",
|
||||
description=tr_noop("<b>Add extra buffer when stopped behind vehicles in a rainstorm.</b> Increase for more room; decrease for shorter gaps."),
|
||||
callback=save_stopped_distance,
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Reduce Acceleration by:"),
|
||||
lambda: self._params.get_int("ReduceAccelerationRainStorm", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=10,
|
||||
step=1,
|
||||
unit=" feet",
|
||||
description=tr_noop("<b>Add extra buffer when stopped behind vehicles in rain.</b> Increase for more room; decrease for shorter gaps."),
|
||||
callback=save_reduce_accel,
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Reduce Acceleration by:"),
|
||||
lambda: self._params.get_int("ReduceAccelerationRain", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=50,
|
||||
step=5,
|
||||
unit="%",
|
||||
description=tr_noop("<b>Lower the maximum acceleration in rain.</b> Increase for softer takeoffs; decrease for quicker but less stable takeoffs."),
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Reduce Speed in Curves by:"),
|
||||
lambda: self._params.get_int("ReduceLateralAccelerationRain", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=50,
|
||||
step=5,
|
||||
unit="%",
|
||||
description=tr_noop(
|
||||
"<b>Lower the desired speed while driving through curves in rain.</b> Increase for safer, gentler turns; decrease for more aggressive driving in curves."
|
||||
),
|
||||
callback=save_reduce_lateral,
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
|
||||
class StarPilotSnowLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
def save_following(value: float):
|
||||
self._params.put_int("IncreaseFollowingSnow", int(value))
|
||||
|
||||
def save_stopped_distance(value: float):
|
||||
self._params.put_int("IncreasedStoppedDistanceSnow", int(value))
|
||||
|
||||
def save_reduce_accel(value: float):
|
||||
self._params.put_int("ReduceAccelerationSnow", int(value))
|
||||
|
||||
def save_reduce_lateral(value: float):
|
||||
self._params.put_int("ReduceLateralAccelerationSnow", int(value))
|
||||
|
||||
items = [
|
||||
value_item(
|
||||
tr_noop("Increase Following Distance by:"),
|
||||
lambda: self._params.get_int("IncreaseFollowingSnow", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=3,
|
||||
step=0.5,
|
||||
unit=" seconds",
|
||||
description=tr_noop("<b>Add extra space behind lead vehicles in snow.</b> Increase for more space; decrease for tighter gaps."),
|
||||
callback=save_following,
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Increase Stopped Distance by:"),
|
||||
lambda: self._params.get_int("IncreasedStoppedDistanceSnow", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=10,
|
||||
step=1,
|
||||
unit=" feet",
|
||||
description=tr_noop("<b>Add extra buffer when stopped behind vehicles in snow.</b> Increase for more room; decrease for shorter gaps."),
|
||||
callback=save_stopped_distance,
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Reduce Acceleration by:"),
|
||||
lambda: self._params.get_int("ReduceAccelerationSnow", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=50,
|
||||
step=5,
|
||||
unit="%",
|
||||
description=tr_noop("<b>Lower the maximum acceleration in snow.</b> Increase for softer takeoffs; decrease for quicker but less stable takeoffs."),
|
||||
callback=save_reduce_accel,
|
||||
),
|
||||
value_item(
|
||||
tr_noop("Reduce Speed in Curves by:"),
|
||||
lambda: self._params.get_int("ReduceLateralAccelerationSnow", return_default=True, default="0"),
|
||||
min_val=0,
|
||||
max_val=50,
|
||||
step=5,
|
||||
unit="%",
|
||||
description=tr_noop(
|
||||
"<b>Lower the desired speed while driving through curves in snow.</b> Increase for safer, gentler turns; decrease for more aggressive driving in curves."
|
||||
),
|
||||
callback=save_reduce_lateral,
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
@@ -0,0 +1,324 @@
|
||||
from __future__ import annotations
|
||||
from collections.abc import Callable
|
||||
import pyray as rl
|
||||
|
||||
from openpilot.common.params import Params
|
||||
from openpilot.system.ui.widgets import Widget
|
||||
from openpilot.system.ui.lib.multilang import tr, tr_noop
|
||||
from openpilot.system.ui.widgets.scroller_tici import Scroller
|
||||
from openpilot.system.ui.widgets.list_view import multiple_button_item, category_buttons_item
|
||||
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.panel import StarPilotPanelType, StarPilotPanelInfo
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.sounds import StarPilotSoundsLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.driving_model import StarPilotDrivingModelLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.longitudinal import StarPilotLongitudinalLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.lateral import StarPilotLateralLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.maps import StarPilotMapsLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.navigation import StarPilotNavigationLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.data import StarPilotDataLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.device import StarPilotDeviceLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.utilities import StarPilotUtilitiesLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.visuals import StarPilotVisualsLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.themes import StarPilotThemesLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.vehicle import StarPilotVehicleSettingsLayout
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.wheel import StarPilotWheelLayout
|
||||
|
||||
STARPILOT_ICONS_DIR = "toggle_icons"
|
||||
|
||||
class StarPilotLayout(Widget):
|
||||
CATEGORIES = [
|
||||
{
|
||||
"title": "Alerts and Sounds",
|
||||
"icon": "icon_sound.png",
|
||||
"desc": "<b>Adjust alert volumes and enable custom notifications.</b>",
|
||||
"buttons": [("MANAGE", "SOUNDS", 0)],
|
||||
},
|
||||
{
|
||||
"title": "Driving Controls",
|
||||
"icon": "icon_steering.png",
|
||||
"desc": "<b>Fine-tune custom StarPilot acceleration, braking, and steering controls.</b>",
|
||||
"buttons": [("DRIVING MODEL", "DRIVING_MODEL", 0), ("GAS / BRAKE", "LONGITUDINAL", 0), ("STEERING", "LATERAL", 0)],
|
||||
},
|
||||
{
|
||||
"title": "Navigation",
|
||||
"icon": "icon_navigate.png",
|
||||
"desc": "<b>Download map data for the Speed Limit Controller.</b>",
|
||||
"buttons": [("MAP DATA", "MAPS", 0), ("NAVIGATION", "NAVIGATION", 1)],
|
||||
},
|
||||
{
|
||||
"title": "System Settings",
|
||||
"icon": "icon_system.png",
|
||||
"desc": "<b>Manage backups, device settings, screen options, storage, and tools to keep StarPilot running smoothly.</b>",
|
||||
"buttons": [("DATA", "DATA", 0), ("DEVICE CONTROLS", "DEVICE", 2), ("UTILITIES", "UTILITIES", 0)],
|
||||
},
|
||||
{
|
||||
"title": "Theme and Appearance",
|
||||
"icon": "icon_display.png",
|
||||
"desc": "<b>Customize the look of the driving screen and interface, including themes!</b>",
|
||||
"buttons": [("APPEARANCE", "VISUALS", 0), ("THEME", "THEMES", 0)],
|
||||
},
|
||||
{
|
||||
"title": "Vehicle Settings",
|
||||
"icon": "icon_vehicle.png",
|
||||
"desc": "<b>Configure car-specific options and steering wheel button mappings.</b>",
|
||||
"buttons": [("VEHICLE SETTINGS", "VEHICLE", 0), ("WHEEL CONTROLS", "WHEEL", 1)],
|
||||
},
|
||||
]
|
||||
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self._params = Params()
|
||||
|
||||
self._current_panel = StarPilotPanelType.MAIN
|
||||
self._depth_callback: Callable | None = None
|
||||
self._settings_layout = None
|
||||
|
||||
self._panel_stack: list[tuple[StarPilotPanelType, str]] = []
|
||||
self._sub_panel_callbacks: dict[str, Callable] = {}
|
||||
|
||||
self._toggle_tuning_levels: dict[str, int] = {}
|
||||
all_keys = self._params.all_keys()
|
||||
for key in all_keys:
|
||||
level = self._params.get_tuning_level(key)
|
||||
if level is not None:
|
||||
self._toggle_tuning_levels[key] = level
|
||||
|
||||
self._panels = {
|
||||
StarPilotPanelType.MAIN: StarPilotPanelInfo("", None),
|
||||
StarPilotPanelType.SOUNDS: StarPilotPanelInfo(tr_noop("Sounds"), StarPilotSoundsLayout()),
|
||||
StarPilotPanelType.DRIVING_MODEL: StarPilotPanelInfo(tr_noop("Driving Model"), StarPilotDrivingModelLayout()),
|
||||
StarPilotPanelType.LONGITUDINAL: StarPilotPanelInfo(tr_noop("Gas / Brake"), StarPilotLongitudinalLayout()),
|
||||
StarPilotPanelType.LATERAL: StarPilotPanelInfo(tr_noop("Steering"), StarPilotLateralLayout()),
|
||||
StarPilotPanelType.MAPS: StarPilotPanelInfo(tr_noop("Map Data"), StarPilotMapsLayout()),
|
||||
StarPilotPanelType.NAVIGATION: StarPilotPanelInfo(tr_noop("Navigation"), StarPilotNavigationLayout()),
|
||||
StarPilotPanelType.DATA: StarPilotPanelInfo(tr_noop("Data Management"), StarPilotDataLayout()),
|
||||
StarPilotPanelType.DEVICE: StarPilotPanelInfo(tr_noop("Device Controls"), StarPilotDeviceLayout()),
|
||||
StarPilotPanelType.UTILITIES: StarPilotPanelInfo(tr_noop("Utilities"), StarPilotUtilitiesLayout()),
|
||||
StarPilotPanelType.VISUALS: StarPilotPanelInfo(tr_noop("Appearance"), StarPilotVisualsLayout()),
|
||||
StarPilotPanelType.THEMES: StarPilotPanelInfo(tr_noop("Themes"), StarPilotThemesLayout()),
|
||||
StarPilotPanelType.VEHICLE: StarPilotPanelInfo(tr_noop("Vehicle Settings"), StarPilotVehicleSettingsLayout()),
|
||||
StarPilotPanelType.WHEEL: StarPilotPanelInfo(tr_noop("Wheel Controls"), StarPilotWheelLayout()),
|
||||
}
|
||||
|
||||
self._setup_longitudinal_sub_panels()
|
||||
self._setup_sounds_sub_panels()
|
||||
self._setup_lateral_sub_panels()
|
||||
|
||||
for panel_type in [
|
||||
StarPilotPanelType.SOUNDS,
|
||||
StarPilotPanelType.DRIVING_MODEL,
|
||||
]:
|
||||
panel = self._panels[panel_type].instance
|
||||
if panel and hasattr(panel, 'set_tuning_levels'):
|
||||
panel.set_tuning_levels(self._toggle_tuning_levels)
|
||||
|
||||
tuning_levels = [tr("Minimal"), tr("Standard"), tr("Advanced"), tr("Developer")]
|
||||
tuning_level_str = self._params.get("TuningLevel", return_default=True, default="1")
|
||||
current_tuning_level = int(tuning_level_str) if tuning_level_str else 1
|
||||
|
||||
items = [
|
||||
multiple_button_item(
|
||||
tr_noop("Tuning Level"),
|
||||
tr_noop(
|
||||
"Choose your tuning level. Lower levels keep it simple; higher levels unlock more toggles for finer control.\n\n"
|
||||
"Minimal - Ideal for those who prefer simplicity or ease of use\n"
|
||||
"Standard - Recommended for most users for a balanced experience\n"
|
||||
"Advanced - Fine-tuning for experienced users\n"
|
||||
"Developer - Highly customizable settings for seasoned enthusiasts"
|
||||
),
|
||||
tuning_levels,
|
||||
current_tuning_level,
|
||||
callback=self._on_tuning_level_changed,
|
||||
icon=f"{STARPILOT_ICONS_DIR}/icon_tuning.png",
|
||||
starpilot_icon=True,
|
||||
),
|
||||
]
|
||||
|
||||
panel_type_map = {
|
||||
"SOUNDS": StarPilotPanelType.SOUNDS,
|
||||
"DRIVING_MODEL": StarPilotPanelType.DRIVING_MODEL,
|
||||
"LONGITUDINAL": StarPilotPanelType.LONGITUDINAL,
|
||||
"LATERAL": StarPilotPanelType.LATERAL,
|
||||
"MAPS": StarPilotPanelType.MAPS,
|
||||
"NAVIGATION": StarPilotPanelType.NAVIGATION,
|
||||
"DATA": StarPilotPanelType.DATA,
|
||||
"DEVICE": StarPilotPanelType.DEVICE,
|
||||
"UTILITIES": StarPilotPanelType.UTILITIES,
|
||||
"VISUALS": StarPilotPanelType.VISUALS,
|
||||
"THEMES": StarPilotPanelType.THEMES,
|
||||
"VEHICLE": StarPilotPanelType.VEHICLE,
|
||||
"WHEEL": StarPilotPanelType.WHEEL,
|
||||
}
|
||||
|
||||
for cat in self.CATEGORIES:
|
||||
filtered_buttons = []
|
||||
for btn_label, panel_key, min_level in cat["buttons"]:
|
||||
if current_tuning_level >= min_level:
|
||||
panel_type = panel_type_map[panel_key]
|
||||
callback = lambda p=panel_type: self._set_current_panel(p)
|
||||
filtered_buttons.append((tr(btn_label), callback))
|
||||
|
||||
if filtered_buttons:
|
||||
full_icon_path = f"{STARPILOT_ICONS_DIR}/{cat['icon']}"
|
||||
item = category_buttons_item(
|
||||
title=tr(cat["title"]),
|
||||
buttons=filtered_buttons,
|
||||
description=tr(cat["desc"]),
|
||||
icon=full_icon_path,
|
||||
starpilot_icon=True,
|
||||
)
|
||||
items.append(item)
|
||||
|
||||
self._main_scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
|
||||
def set_depth_callback(self, callback: Callable):
|
||||
self._depth_callback = callback
|
||||
|
||||
def set_settings_layout(self, settings_layout):
|
||||
self._settings_layout = settings_layout
|
||||
|
||||
def navigate_back(self):
|
||||
if self._panel_stack:
|
||||
self._panel_stack.pop()
|
||||
if self._panel_stack:
|
||||
self._update_sub_panel_visibility()
|
||||
else:
|
||||
self._set_current_panel(StarPilotPanelType.MAIN)
|
||||
|
||||
def _push_sub_panel(self, sub_panel_name: str):
|
||||
self._panel_stack.append((self._current_panel, sub_panel_name))
|
||||
self._update_sub_panel_visibility()
|
||||
|
||||
def _update_sub_panel_visibility(self):
|
||||
if self._current_panel == StarPilotPanelType.LONGITUDINAL:
|
||||
longitudinal = self._panels[StarPilotPanelType.LONGITUDINAL].instance
|
||||
if longitudinal:
|
||||
current_sub = self._get_current_sub_panel()
|
||||
if hasattr(longitudinal, 'set_current_sub_panel'):
|
||||
longitudinal.set_current_sub_panel(current_sub)
|
||||
elif self._current_panel == StarPilotPanelType.SOUNDS:
|
||||
sounds = self._panels[StarPilotPanelType.SOUNDS].instance
|
||||
if sounds:
|
||||
current_sub = self._get_current_sub_panel()
|
||||
if hasattr(sounds, '_navigate_to'):
|
||||
sounds._current_sub_panel = current_sub
|
||||
|
||||
def _get_current_sub_panel(self) -> str:
|
||||
if self._panel_stack and self._panel_stack[-1][0] == self._current_panel:
|
||||
return self._panel_stack[-1][1]
|
||||
return ""
|
||||
|
||||
def _setup_longitudinal_sub_panels(self):
|
||||
longitudinal = self._panels[StarPilotPanelType.LONGITUDINAL].instance
|
||||
if longitudinal and hasattr(longitudinal, 'set_navigate_callback'):
|
||||
longitudinal.set_navigate_callback(self._push_sub_panel)
|
||||
|
||||
def _setup_sounds_sub_panels(self):
|
||||
sounds = self._panels[StarPilotPanelType.SOUNDS].instance
|
||||
if sounds and hasattr(sounds, 'set_navigate_callback'):
|
||||
sounds.set_navigate_callback(self._push_sub_panel)
|
||||
|
||||
def _setup_lateral_sub_panels(self):
|
||||
lateral = self._panels[StarPilotPanelType.LATERAL].instance
|
||||
if lateral and hasattr(lateral, 'set_navigate_callback'):
|
||||
lateral.set_navigate_callback(self._push_sub_panel)
|
||||
|
||||
def _on_tuning_level_changed(self, index: int):
|
||||
self._params.put_nonblocking("TuningLevel", index)
|
||||
if self._settings_layout:
|
||||
self._settings_layout.refresh_developer_visibility()
|
||||
for panel_info in self._panels.values():
|
||||
panel = panel_info.instance
|
||||
if panel and hasattr(panel, 'refresh_visibility'):
|
||||
panel.refresh_visibility()
|
||||
self._rebuild_main_scroller(index)
|
||||
|
||||
def _rebuild_main_scroller(self, tuning_level: int):
|
||||
tuning_levels = [tr("Minimal"), tr("Standard"), tr("Advanced"), tr("Developer")]
|
||||
|
||||
items = [
|
||||
multiple_button_item(
|
||||
tr_noop("Tuning Level"),
|
||||
tr_noop(
|
||||
"Choose your tuning level. Lower levels keep it simple; higher levels unlock more toggles for finer control.\n\n"
|
||||
"Minimal - Ideal for those who prefer simplicity or ease of use\n"
|
||||
"Standard - Recommended for most users for a balanced experience\n"
|
||||
"Advanced - Fine-tuning for experienced users\n"
|
||||
"Developer - Highly customizable settings for seasoned enthusiasts"
|
||||
),
|
||||
tuning_levels,
|
||||
tuning_level,
|
||||
callback=self._on_tuning_level_changed,
|
||||
icon=f"{STARPILOT_ICONS_DIR}/icon_tuning.png",
|
||||
starpilot_icon=True,
|
||||
),
|
||||
]
|
||||
|
||||
panel_type_map = {
|
||||
"SOUNDS": StarPilotPanelType.SOUNDS,
|
||||
"DRIVING_MODEL": StarPilotPanelType.DRIVING_MODEL,
|
||||
"LONGITUDINAL": StarPilotPanelType.LONGITUDINAL,
|
||||
"LATERAL": StarPilotPanelType.LATERAL,
|
||||
"MAPS": StarPilotPanelType.MAPS,
|
||||
"NAVIGATION": StarPilotPanelType.NAVIGATION,
|
||||
"DATA": StarPilotPanelType.DATA,
|
||||
"DEVICE": StarPilotPanelType.DEVICE,
|
||||
"UTILITIES": StarPilotPanelType.UTILITIES,
|
||||
"VISUALS": StarPilotPanelType.VISUALS,
|
||||
"THEMES": StarPilotPanelType.THEMES,
|
||||
"VEHICLE": StarPilotPanelType.VEHICLE,
|
||||
"WHEEL": StarPilotPanelType.WHEEL,
|
||||
}
|
||||
|
||||
for cat in self.CATEGORIES:
|
||||
filtered_buttons = []
|
||||
for btn_label, panel_key, min_level in cat["buttons"]:
|
||||
if tuning_level >= min_level:
|
||||
panel_type = panel_type_map[panel_key]
|
||||
callback = lambda p=panel_type: self._set_current_panel(p)
|
||||
filtered_buttons.append((tr(btn_label), callback))
|
||||
|
||||
if filtered_buttons:
|
||||
full_icon_path = f"{STARPILOT_ICONS_DIR}/{cat['icon']}"
|
||||
item = category_buttons_item(
|
||||
title=tr(cat["title"]),
|
||||
buttons=filtered_buttons,
|
||||
description=tr(cat["desc"]),
|
||||
icon=full_icon_path,
|
||||
starpilot_icon=True,
|
||||
)
|
||||
items.append(item)
|
||||
|
||||
self._main_scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
|
||||
def _set_current_panel(self, panel_type: StarPilotPanelType):
|
||||
if panel_type != self._current_panel:
|
||||
if self._current_panel != StarPilotPanelType.MAIN:
|
||||
self._panels[self._current_panel].instance.hide_event()
|
||||
self._current_panel = panel_type
|
||||
if panel_type != StarPilotPanelType.MAIN:
|
||||
self._panels[panel_type].instance.show_event()
|
||||
|
||||
depth = 1 if panel_type != StarPilotPanelType.MAIN else 0
|
||||
if self._depth_callback:
|
||||
self._depth_callback(depth)
|
||||
|
||||
def _render(self, rect: rl.Rectangle):
|
||||
if self._current_panel == StarPilotPanelType.MAIN:
|
||||
self._main_scroller.render(rect)
|
||||
else:
|
||||
panel = self._panels[self._current_panel]
|
||||
if panel.instance:
|
||||
panel.instance.render(rect)
|
||||
|
||||
def show_event(self):
|
||||
super().show_event()
|
||||
if self._current_panel == StarPilotPanelType.MAIN:
|
||||
self._main_scroller.show_event()
|
||||
else:
|
||||
self._panels[self._current_panel].instance.show_event()
|
||||
|
||||
def hide_event(self):
|
||||
super().hide_event()
|
||||
if self._current_panel != StarPilotPanelType.MAIN:
|
||||
self._panels[self._current_panel].instance.hide_event()
|
||||
@@ -0,0 +1,25 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from openpilot.system.ui.lib.multilang import tr, tr_noop
|
||||
from openpilot.system.ui.widgets.list_view import button_item
|
||||
from openpilot.system.ui.widgets.scroller_tici import Scroller
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.panel import StarPilotPanel
|
||||
|
||||
class StarPilotMapsLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
items = [
|
||||
button_item(
|
||||
tr_noop("Download Map Data"),
|
||||
lambda: tr("DOWNLOAD"),
|
||||
tr_noop("<b>Download map data</b> for the Speed Limit Controller."),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Manage Map Data"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>View or delete downloaded map data.</b>"),
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
@@ -0,0 +1,25 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from openpilot.system.ui.lib.multilang import tr, tr_noop
|
||||
from openpilot.system.ui.widgets.list_view import toggle_item, button_item
|
||||
from openpilot.system.ui.widgets.scroller_tici import Scroller
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.panel import StarPilotPanel
|
||||
|
||||
class StarPilotNavigationLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
items = [
|
||||
toggle_item(
|
||||
tr_noop("Use Live Map Data"),
|
||||
tr_noop("<b>Use live map data</b> for real-time navigation updates."),
|
||||
False,
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Navigation Settings"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Configure navigation-specific options</b> like route preferences."),
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
@@ -0,0 +1,74 @@
|
||||
from __future__ import annotations
|
||||
from collections.abc import Callable
|
||||
from dataclasses import dataclass
|
||||
from enum import IntEnum
|
||||
|
||||
import pyray as rl
|
||||
|
||||
from openpilot.common.params import Params
|
||||
from openpilot.system.ui.widgets import Widget
|
||||
|
||||
class StarPilotPanelType(IntEnum):
|
||||
MAIN = 0
|
||||
SOUNDS = 1
|
||||
DRIVING_MODEL = 2
|
||||
LONGITUDINAL = 3
|
||||
LATERAL = 4
|
||||
MAPS = 5
|
||||
NAVIGATION = 6
|
||||
DATA = 7
|
||||
DEVICE = 8
|
||||
UTILITIES = 9
|
||||
VISUALS = 10
|
||||
THEMES = 11
|
||||
VEHICLE = 12
|
||||
WHEEL = 13
|
||||
|
||||
@dataclass
|
||||
class StarPilotPanelInfo:
|
||||
name: str
|
||||
instance: Widget
|
||||
|
||||
class StarPilotPanel(Widget):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self._params = Params()
|
||||
self._params_memory = Params(memory=True)
|
||||
self._tuning_levels: dict[str, int] = {}
|
||||
self._navigate_callback: Callable | None = None
|
||||
self._back_callback: Callable | None = None
|
||||
self._current_sub_panel = ""
|
||||
self._sub_panels: dict[str, Widget] = {}
|
||||
self._scroller = None
|
||||
|
||||
def set_navigate_callback(self, callback: Callable):
|
||||
self._navigate_callback = callback
|
||||
|
||||
def set_back_callback(self, callback: Callable):
|
||||
self._back_callback = callback
|
||||
|
||||
def set_tuning_levels(self, levels: dict[str, int]):
|
||||
self._tuning_levels = levels
|
||||
|
||||
def _navigate_to(self, sub_panel: str):
|
||||
self._current_sub_panel = sub_panel
|
||||
if self._navigate_callback:
|
||||
self._navigate_callback(sub_panel)
|
||||
|
||||
def _go_back(self):
|
||||
self._current_sub_panel = ""
|
||||
if self._back_callback:
|
||||
self._back_callback()
|
||||
|
||||
def _render(self, rect: rl.Rectangle):
|
||||
if self._current_sub_panel and self._current_sub_panel in self._sub_panels:
|
||||
self._sub_panels[self._current_sub_panel].render(rect)
|
||||
elif self._scroller:
|
||||
self._scroller.render(rect)
|
||||
|
||||
def show_event(self):
|
||||
super().show_event()
|
||||
if self._current_sub_panel and self._current_sub_panel in self._sub_panels:
|
||||
self._sub_panels[self._current_sub_panel].show_event()
|
||||
elif self._scroller:
|
||||
self._scroller.show_event()
|
||||
@@ -0,0 +1,271 @@
|
||||
from __future__ import annotations
|
||||
import subprocess
|
||||
from pathlib import Path
|
||||
|
||||
from openpilot.common.basedir import BASEDIR
|
||||
from openpilot.frogpilot.common.frogpilot_variables import ACTIVE_THEME_PATH
|
||||
from openpilot.system.ui.lib.multilang import tr, tr_noop
|
||||
from openpilot.system.ui.widgets.list_view import button_item, toggle_item, value_button_item
|
||||
from openpilot.system.ui.widgets.scroller_tici import Scroller
|
||||
from openpilot.selfdrive.ui.ui_state import ui_state
|
||||
from openpilot.selfdrive.ui.lib.starpilot_state import starpilot_state
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.panel import StarPilotPanel
|
||||
|
||||
class StarPilotSoundsLayout(StarPilotPanel):
|
||||
VOLUME_KEYS = [
|
||||
"DisengageVolume",
|
||||
"EngageVolume",
|
||||
"PromptVolume",
|
||||
"PromptDistractedVolume",
|
||||
"RefuseVolume",
|
||||
"WarningSoftVolume",
|
||||
"WarningImmediateVolume",
|
||||
]
|
||||
CUSTOM_ALERTS_KEYS = [
|
||||
"GoatScream",
|
||||
"GreenLightAlert",
|
||||
"LeadDepartingAlert",
|
||||
"LoudBlindspotAlert",
|
||||
"SpeedLimitChangedAlert",
|
||||
]
|
||||
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
items = [
|
||||
button_item(
|
||||
tr_noop("Alert Volume Controller"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Set how loud each type of openpilot alert is</b> to keep routine prompts from becoming distracting."),
|
||||
callback=lambda: self._navigate_to("volume_control"),
|
||||
icon="toggle_icons/icon_mute.png",
|
||||
starpilot_icon=True,
|
||||
),
|
||||
button_item(
|
||||
tr_noop("StarPilot Alerts"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Optional StarPilot alerts</b> that highlight driving events in a more noticeable way."),
|
||||
callback=lambda: self._navigate_to("custom_alerts"),
|
||||
icon="toggle_icons/icon_green_light.png",
|
||||
starpilot_icon=True,
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
|
||||
self._sub_panels = {
|
||||
"volume_control": StarPilotVolumeControlLayout(),
|
||||
"custom_alerts": StarPilotCustomAlertsLayout(),
|
||||
}
|
||||
|
||||
# Wire up navigation callbacks for sub-panels
|
||||
for name, panel in self._sub_panels.items():
|
||||
if hasattr(panel, 'set_navigate_callback'):
|
||||
panel.set_navigate_callback(self._navigate_to)
|
||||
if hasattr(panel, 'set_back_callback'):
|
||||
panel.set_back_callback(self._go_back)
|
||||
|
||||
def refresh_visibility(self):
|
||||
for panel in self._sub_panels.values():
|
||||
if hasattr(panel, 'refresh_visibility'):
|
||||
panel.refresh_visibility()
|
||||
|
||||
class StarPilotVolumeControlLayout(StarPilotPanel):
|
||||
VOLUME_INFO = {
|
||||
"DisengageVolume": {
|
||||
"title": tr_noop("Disengage Volume"),
|
||||
"desc": tr_noop(
|
||||
"<b>Set the volume for alerts when openpilot disengages.</b><br><br>Examples include: \"Cruise Fault: Restart the Car\", \"Parking Brake Engaged\", \"Pedal Pressed\"."
|
||||
),
|
||||
"min": 0,
|
||||
},
|
||||
"EngageVolume": {
|
||||
"title": tr_noop("Engage Volume"),
|
||||
"desc": tr_noop("<b>Set the volume for the chime when openpilot engages</b>, such as after pressing the \"RESUME\" or \"SET\" steering wheel buttons."),
|
||||
"min": 0,
|
||||
},
|
||||
"PromptVolume": {
|
||||
"title": tr_noop("Prompt Volume"),
|
||||
"desc": tr_noop(
|
||||
"<b>Set the volume for prompts that need attention.</b><br><br>Examples include: \"Car Detected in Blindspot\", \"Steering Temporarily Unavailable\", \"Turn Exceeds Steering Limit\"."
|
||||
),
|
||||
"min": 0,
|
||||
},
|
||||
"PromptDistractedVolume": {
|
||||
"title": tr_noop("Prompt Distracted Volume"),
|
||||
"desc": tr_noop(
|
||||
"<b>Set the volume for prompts when openpilot detects driver distraction or unresponsiveness.</b><br><br>Examples include: \"Pay Attention\", \"Touch Steering Wheel\"."
|
||||
),
|
||||
"min": 0,
|
||||
},
|
||||
"RefuseVolume": {
|
||||
"title": tr_noop("Refuse Volume"),
|
||||
"desc": tr_noop(
|
||||
"<b>Set the volume for alerts when openpilot refuses to engage.</b><br><br>Examples include: \"Brake Hold Active\", \"Door Open\", \"Seatbelt Unlatched\"."
|
||||
),
|
||||
"min": 0,
|
||||
},
|
||||
"WarningSoftVolume": {
|
||||
"title": tr_noop("Warning Soft Volume"),
|
||||
"desc": tr_noop(
|
||||
"<b>Set the volume for softer warnings about potential risks.</b><br><br>Examples include: \"BRAKE! Risk of Collision\", \"Steering Temporarily Unavailable\"."
|
||||
),
|
||||
"min": 25,
|
||||
},
|
||||
"WarningImmediateVolume": {
|
||||
"title": tr_noop("Warning Immediate Volume"),
|
||||
"desc": tr_noop(
|
||||
"<b>Set the volume for the loudest warnings that require urgent attention.</b><br><br>Examples include: \"DISENGAGE IMMEDIATELY — Driver Distracted\", \"DISENGAGE IMMEDIATELY — Driver Unresponsive\"."
|
||||
),
|
||||
"min": 25,
|
||||
},
|
||||
}
|
||||
|
||||
_sound_player_process = None
|
||||
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self._init_sound_player()
|
||||
|
||||
volume_labels = {0.0: tr("Muted"), 101.0: tr("Auto")}
|
||||
for i in range(1, 101):
|
||||
volume_labels[float(i)] = f"{i}%"
|
||||
|
||||
items = []
|
||||
for key in StarPilotSoundsLayout.VOLUME_KEYS:
|
||||
info = self.VOLUME_INFO[key]
|
||||
items.append(
|
||||
value_button_item(
|
||||
info["title"],
|
||||
key,
|
||||
min_val=info["min"],
|
||||
max_val=101,
|
||||
step=1,
|
||||
button_text="Test",
|
||||
button_callback=lambda k=key: self._test_sound(k),
|
||||
description=info["desc"],
|
||||
labels=volume_labels,
|
||||
)
|
||||
)
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
|
||||
@classmethod
|
||||
def _init_sound_player(cls):
|
||||
if cls._sound_player_process is not None:
|
||||
return
|
||||
|
||||
program = """
|
||||
import numpy as np
|
||||
import sounddevice as sd
|
||||
import sys
|
||||
import wave
|
||||
|
||||
while True:
|
||||
try:
|
||||
line = sys.stdin.readline()
|
||||
if not line:
|
||||
break
|
||||
path, volume = line.strip().split('|')
|
||||
|
||||
sound_file = wave.open(path, 'rb')
|
||||
audio = np.frombuffer(sound_file.readframes(sound_file.getnframes()), dtype=np.int16).astype(np.float32) / 32768.0
|
||||
|
||||
sd.play(audio * float(volume), sound_file.getframerate())
|
||||
sd.wait()
|
||||
except Exception:
|
||||
pass
|
||||
"""
|
||||
|
||||
cls._sound_player_process = subprocess.Popen(
|
||||
["python3", "-u", "-c", program],
|
||||
stdin=subprocess.PIPE,
|
||||
stdout=subprocess.DEVNULL,
|
||||
stderr=subprocess.DEVNULL,
|
||||
)
|
||||
|
||||
def _play_sound_offroad(self, key: str):
|
||||
base_name = key.replace("Volume", "")
|
||||
snake_case = "".join(["_" + c.lower() if c.isupper() else c for c in base_name]).lstrip("_")
|
||||
stock_path = Path(BASEDIR) / "selfdrive" / "assets" / "sounds" / f"{snake_case}.wav"
|
||||
theme_path = ACTIVE_THEME_PATH / "sounds" / f"{snake_case}.wav"
|
||||
|
||||
sound_path = theme_path if theme_path.exists() else stock_path
|
||||
if not sound_path.exists():
|
||||
return
|
||||
|
||||
volume = self._params.get_int(key, return_default=True, default=100) / 100.0
|
||||
|
||||
try:
|
||||
self._sound_player_process.stdin.write(f"{sound_path}|{volume}\n".encode())
|
||||
self._sound_player_process.stdin.flush()
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
def _test_sound(self, key: str):
|
||||
base_name = key.replace("Volume", "")
|
||||
if ui_state.started:
|
||||
camel_case = base_name[0].lower() + base_name[1:]
|
||||
self._params_memory.put("TestAlert", camel_case)
|
||||
else:
|
||||
self._play_sound_offroad(key)
|
||||
|
||||
class StarPilotCustomAlertsLayout(StarPilotPanel):
|
||||
ALERT_INFO = {
|
||||
"GoatScream": {
|
||||
"title": tr_noop("Goat Scream"),
|
||||
"desc": tr_noop(
|
||||
"<b>Play the infamous \"Goat Scream\" when the steering controller reaches its limit.</b> Based on the \"Turn Exceeds Steering Limit\" event."
|
||||
),
|
||||
},
|
||||
"GreenLightAlert": {
|
||||
"title": tr_noop("Green Light Alert"),
|
||||
"desc": tr_noop(
|
||||
"<b>Play an alert when the model predicts a red light has turned green.</b><br><br><i><b>Disclaimer</b>: openpilot does not explicitly detect traffic lights. This alert is based on end-to-end model predictions from camera input and may trigger even when the light has not changed.</i>"
|
||||
),
|
||||
},
|
||||
"LeadDepartingAlert": {
|
||||
"title": tr_noop("Lead Departing Alert"),
|
||||
"desc": tr_noop("<b>Play an alert when the lead vehicle departs from a stop.</b>"),
|
||||
},
|
||||
"LoudBlindspotAlert": {
|
||||
"title": tr_noop("Loud \"Car Detected in Blindspot\" Alert"),
|
||||
"desc": tr_noop(
|
||||
"<b>Play a louder alert if a vehicle is in the blind spot when attempting to change lanes.</b> Based on the \"Car Detected in Blindspot\" event."
|
||||
),
|
||||
},
|
||||
"SpeedLimitChangedAlert": {
|
||||
"title": tr_noop("Speed Limit Changed Alert"),
|
||||
"desc": tr_noop("<b>Play an alert when the posted speed limit changes.</b>"),
|
||||
},
|
||||
}
|
||||
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self._toggle_items = {}
|
||||
|
||||
for key in StarPilotSoundsLayout.CUSTOM_ALERTS_KEYS:
|
||||
info = self.ALERT_INFO[key]
|
||||
self._toggle_items[key] = toggle_item(
|
||||
info["title"],
|
||||
info["desc"],
|
||||
self._params.get_bool(key),
|
||||
callback=lambda s, k=key: self._params.put_bool(k, s),
|
||||
)
|
||||
|
||||
self._scroller = Scroller(list(self._toggle_items.values()), line_separator=True, spacing=0)
|
||||
|
||||
def refresh_visibility(self):
|
||||
current_level = int(self._params.get("TuningLevel", return_default=True, default="1") or "1")
|
||||
for key, item in self._toggle_items.items():
|
||||
min_level = self._tuning_levels.get(key, 0)
|
||||
visible = current_level >= min_level
|
||||
|
||||
if key == "LoudBlindspotAlert":
|
||||
visible &= starpilot_state.car_state.hasBSM
|
||||
elif key == "SpeedLimitChangedAlert":
|
||||
visible &= self._params.get_bool("ShowSpeedLimits") or (
|
||||
starpilot_state.car_state.hasOpenpilotLongitudinal and self._params.get_bool("SpeedLimitController")
|
||||
)
|
||||
|
||||
item.set_visible(visible)
|
||||
@@ -0,0 +1,30 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from openpilot.system.ui.lib.multilang import tr, tr_noop
|
||||
from openpilot.system.ui.widgets.list_view import button_item
|
||||
from openpilot.system.ui.widgets.scroller_tici import Scroller
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.panel import StarPilotPanel
|
||||
|
||||
class StarPilotThemesLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
items = [
|
||||
button_item(
|
||||
tr_noop("Select Theme"),
|
||||
lambda: tr("SELECT"),
|
||||
tr_noop("<b>Select a theme</b> for the StarPilot interface."),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Holiday Themes"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Enable or disable holiday-themed visuals.</b>"),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Custom Theme"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Create or import a custom theme.</b>"),
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
@@ -0,0 +1,30 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from openpilot.system.ui.lib.multilang import tr, tr_noop
|
||||
from openpilot.system.ui.widgets.list_view import button_item
|
||||
from openpilot.system.ui.widgets.scroller_tici import Scroller
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.panel import StarPilotPanel
|
||||
|
||||
class StarPilotUtilitiesLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
items = [
|
||||
button_item(
|
||||
tr_noop("Update StarPilot"),
|
||||
lambda: tr("CHECK"),
|
||||
tr_noop("<b>Check for updates</b> and update StarPilot to the latest version."),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Reset Settings"),
|
||||
lambda: tr("RESET"),
|
||||
tr_noop("<b>Reset all StarPilot settings</b> to their default values."),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("View Logs"),
|
||||
lambda: tr("VIEW"),
|
||||
tr_noop("<b>View StarPilot logs</b> for debugging."),
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
@@ -0,0 +1,20 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from openpilot.system.ui.lib.multilang import tr, tr_noop
|
||||
from openpilot.system.ui.widgets.list_view import button_item
|
||||
from openpilot.system.ui.widgets.scroller_tici import Scroller
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.panel import StarPilotPanel
|
||||
|
||||
class StarPilotVehicleSettingsLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
items = [
|
||||
button_item(
|
||||
tr_noop("Vehicle Settings"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Configure car-specific options</b> like model name and features."),
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
@@ -0,0 +1,40 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from openpilot.system.ui.lib.multilang import tr, tr_noop
|
||||
from openpilot.system.ui.widgets.list_view import button_item
|
||||
from openpilot.system.ui.widgets.scroller_tici import Scroller
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.panel import StarPilotPanel
|
||||
|
||||
class StarPilotVisualsLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
items = [
|
||||
button_item(
|
||||
tr_noop("Advanced UI Controls"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Advanced visual changes</b> to fine-tune how the driving screen looks."),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Driving Screen Widgets"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Custom StarPilot widgets</b> for the driving screen."),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Model UI"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Model visualizations</b> for the driving path, lane lines, path edges, and road edges."),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Navigation Widgets"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Speed limits, and other navigation widgets.</b>"),
|
||||
),
|
||||
button_item(
|
||||
tr_noop("Quality of Life"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Miscellaneous visual changes</b> to fine-tune how the driving screen looks."),
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
@@ -0,0 +1,20 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from openpilot.system.ui.lib.multilang import tr, tr_noop
|
||||
from openpilot.system.ui.widgets.list_view import button_item
|
||||
from openpilot.system.ui.widgets.scroller_tici import Scroller
|
||||
from openpilot.selfdrive.ui.layouts.settings.starpilot.panel import StarPilotPanel
|
||||
|
||||
class StarPilotWheelLayout(StarPilotPanel):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
|
||||
items = [
|
||||
button_item(
|
||||
tr_noop("Wheel Controls"),
|
||||
lambda: tr("MANAGE"),
|
||||
tr_noop("<b>Configure steering wheel button mappings</b> for custom controls."),
|
||||
),
|
||||
]
|
||||
|
||||
self._scroller = Scroller(items, line_separator=True, spacing=0)
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user