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openpilot v0.7.5 release

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This commit is contained in:
Vehicle Researcher
2020-05-09 13:01:35 -07:00
parent 7e908db510
commit ddee718536
237 changed files with 16444 additions and 5626 deletions
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common/transformations/camera.py
-79
View File
@@ -1,6 +1,5 @@
import numpy as np
import common.transformations.orientation as orient
import math
FULL_FRAME_SIZE = (1164, 874)
W, H = FULL_FRAME_SIZE[0], FULL_FRAME_SIZE[1]
@@ -147,81 +146,3 @@ def pretransform_from_calib(calib):
camera_frame_from_calib_frame = get_camera_frame_from_calib_frame(camera_frame_from_road_frame)
return np.linalg.inv(camera_frame_from_calib_frame)
def transform_img(base_img,
augment_trans=np.array([0,0,0]),
augment_eulers=np.array([0,0,0]),
from_intr=eon_intrinsics,
to_intr=eon_intrinsics,
output_size=None,
pretransform=None,
top_hacks=False,
yuv=False,
alpha=1.0,
beta=0,
blur=0):
import cv2 # pylint: disable=import-error
cv2.setNumThreads(1)
if yuv:
base_img = cv2.cvtColor(base_img, cv2.COLOR_YUV2RGB_I420)
size = base_img.shape[:2]
if not output_size:
output_size = size[::-1]
cy = from_intr[1,2]
def get_M(h=1.22):
quadrangle = np.array([[0, cy + 20],
[size[1]-1, cy + 20],
[0, size[0]-1],
[size[1]-1, size[0]-1]], dtype=np.float32)
quadrangle_norm = np.hstack((normalize(quadrangle, intrinsics=from_intr), np.ones((4,1))))
quadrangle_world = np.column_stack((h*quadrangle_norm[:,0]/quadrangle_norm[:,1],
h*np.ones(4),
h/quadrangle_norm[:,1]))
rot = orient.rot_from_euler(augment_eulers)
to_extrinsics = np.hstack((rot.T, -augment_trans[:,None]))
to_KE = to_intr.dot(to_extrinsics)
warped_quadrangle_full = np.einsum('jk,ik->ij', to_KE, np.hstack((quadrangle_world, np.ones((4,1)))))
warped_quadrangle = np.column_stack((warped_quadrangle_full[:,0]/warped_quadrangle_full[:,2],
warped_quadrangle_full[:,1]/warped_quadrangle_full[:,2])).astype(np.float32)
M = cv2.getPerspectiveTransform(quadrangle, warped_quadrangle.astype(np.float32))
return M
M = get_M()
if pretransform is not None:
M = M.dot(pretransform)
augmented_rgb = cv2.warpPerspective(base_img, M, output_size, borderMode=cv2.BORDER_REPLICATE)
if top_hacks:
cyy = int(math.ceil(to_intr[1,2]))
M = get_M(1000)
if pretransform is not None:
M = M.dot(pretransform)
augmented_rgb[:cyy] = cv2.warpPerspective(base_img, M, (output_size[0], cyy), borderMode=cv2.BORDER_REPLICATE)
# brightness and contrast augment
augmented_rgb = np.clip((float(alpha)*augmented_rgb + beta), 0, 255).astype(np.uint8)
# gaussian blur
if blur > 0:
augmented_rgb = cv2.GaussianBlur(augmented_rgb,(blur*2+1,blur*2+1),cv2.BORDER_DEFAULT)
if yuv:
augmented_img = cv2.cvtColor(augmented_rgb, cv2.COLOR_RGB2YUV_I420)
else:
augmented_img = augmented_rgb
return augmented_img
def yuv_crop(frame, output_size, center=None):
# output_size in camera coordinates so u,v
# center in array coordinates so row, column
import cv2 # pylint: disable=import-error
rgb = cv2.cvtColor(frame, cv2.COLOR_YUV2RGB_I420)
if not center:
center = (rgb.shape[0]/2, rgb.shape[1]/2)
rgb_crop = rgb[center[0] - output_size[1]/2: center[0] + output_size[1]/2,
center[1] - output_size[0]/2: center[1] + output_size[0]/2]
return cv2.cvtColor(rgb_crop, cv2.COLOR_RGB2YUV_I420)
common/transformations/model.py
+3 -11
View File
@@ -44,24 +44,15 @@ medmodel_intrinsics = np.array(
# BIG model
BIGMODEL_INPUT_SIZE = (864, 288)
BIGMODEL_INPUT_SIZE = (1024, 512)
BIGMODEL_YUV_SIZE = (BIGMODEL_INPUT_SIZE[0], BIGMODEL_INPUT_SIZE[1] * 3 // 2)
bigmodel_zoom = 1.
bigmodel_intrinsics = np.array(
[[ eon_focal_length / bigmodel_zoom, 0. , 0.5 * BIGMODEL_INPUT_SIZE[0]],
[ 0. , eon_focal_length / bigmodel_zoom, 0.2 * BIGMODEL_INPUT_SIZE[1]],
[ 0. , eon_focal_length / bigmodel_zoom, 256+MEDMODEL_CY],
[ 0. , 0. , 1.]])
bigmodel_border = np.array([
[0,0,1],
[BIGMODEL_INPUT_SIZE[0], 0, 1],
[BIGMODEL_INPUT_SIZE[0], BIGMODEL_INPUT_SIZE[1], 1],
[0, BIGMODEL_INPUT_SIZE[1], 1],
])
model_frame_from_road_frame = np.dot(model_intrinsics,
get_view_frame_from_road_frame(0, 0, 0, model_height))
@@ -72,6 +63,7 @@ medmodel_frame_from_road_frame = np.dot(medmodel_intrinsics,
get_view_frame_from_road_frame(0, 0, 0, model_height))
model_frame_from_bigmodel_frame = np.dot(model_intrinsics, np.linalg.inv(bigmodel_intrinsics))
medmodel_frame_from_bigmodel_frame = np.dot(medmodel_intrinsics, np.linalg.inv(bigmodel_intrinsics))
# 'camera from model camera'
def get_model_height_transform(camera_frame_from_road_frame, height):