promotion

scripts/speed_limit_vision/evaluate_runtime_manifest.py

@@ -28,6 +28,7 @@ def parse_args() -> argparse.Namespace:
   parser.add_argument("--detector-min-confidence", type=float, help="Override runtime US detector confidence threshold.")
   parser.add_argument("--classifier-min-confidence", type=float, help="Override runtime US classifier confidence threshold.")
   parser.add_argument("--classifier-reject-min-confidence", type=float, help="Override runtime reject-class confidence threshold.")
+  parser.add_argument("--include-uncertain", action="store_true", help="Include uncertain_positive review rows in positive metrics.")
   parser.add_argument("--strict-positive-recall", type=float, help="Exit non-zero if positive exact recall is below this value.")
   parser.add_argument("--strict-negative-fpr", type=float, help="Exit non-zero if negative false-positive rate is above this value.")
   return parser.parse_args()
@@ -89,6 +90,15 @@ def main() -> int:
     raise FileNotFoundError(classifier_path)
 
   rows = load_rows(args.manifest.expanduser().resolve(), set(args.split) if args.split else None)
+  uncertain_count = sum(
+    row.get("sample_type", "") == "uncertain_positive" or row.get("review_status", "") == "uncertain"
+    for row in rows
+  )
+  if not args.include_uncertain:
+    rows = [
+      row for row in rows
+      if row.get("sample_type", "") != "uncertain_positive" and row.get("review_status", "") != "uncertain"
+    ]
   if args.max_rows > 0 and len(rows) > args.max_rows:
     rng = random.Random(args.seed)
     rows = rng.sample(rows, args.max_rows)
@@ -159,6 +169,8 @@ def main() -> int:
   negative_fpr = negative_false_positive / negative_count if negative_count else 0.0
 
   print(f"Rows evaluated: {positive_count + negative_count}")
+  if uncertain_count and not args.include_uncertain:
+    print(f"Skipped uncertain rows: {uncertain_count}")
   print(f"Unreadable rows: {unreadable_count}")
   print(
     f"Positive exact: {positive_exact}/{positive_count} "

scripts/speed_limit_vision/import_manifest_classifier_masks.py

@@ -44,6 +44,12 @@ def safe_stem(text: str) -> str:
   return cleaned.strip("._")[:180] or "sample"
 
 
+def short_stem(text: str, max_prefix: int = 80) -> str:
+  prefix = safe_stem(text)[:max_prefix].strip("._") or "sample"
+  digest = hashlib.sha1(text.encode("utf-8")).hexdigest()[:12]
+  return f"{prefix}_{digest}"
+
+
 def read_rows(path: Path) -> list[dict[str, str]]:
   with path.open("r", encoding="utf-8", newline="") as csv_file:
     return list(csv.DictReader(csv_file))
@@ -163,9 +169,9 @@ def load_crop(row: dict[str, str], manifest_path: Path, default_padding: float):
   return crop_box(image, boxes[bbox_index], padding)
 
 
-def write_mask(workspace: Path, split: str, speed_value: int, stem: str, image_bgr) -> None:
+def write_mask(workspace: Path, split: str, speed_value: int, stem: str, image_bgr) -> bool:
   output_dir = ensure_dir(workspace / "classifier" / split / str(speed_value))
-  cv2.imwrite(str(output_dir / f"{stem}.png"), image_bgr)
+  return cv2.imwrite(str(output_dir / f"{stem}.png"), image_bgr)
 
 
 def main() -> int:
@@ -178,6 +184,7 @@ def main() -> int:
   skipped_no_speed = 0
   skipped_no_crop = 0
   skipped_no_mask = 0
+  skipped_write_failed = 0
   written = 0
 
   for manifest_path in [path.expanduser().resolve() for path in args.manifest]:
@@ -207,25 +214,32 @@ def main() -> int:
         skipped_no_mask += 1
         continue
 
-      manifest_stem = safe_stem(manifest_path.stem)
-      source_stem = safe_stem(key_text)
+      manifest_stem = short_stem(manifest_path.stem, max_prefix=48)
+      source_stem = short_stem(key_text, max_prefix=72)
       base_stem = f"manifest_{manifest_stem}_{row_index:06d}_{source_stem}"
       base_mask = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
-      write_mask(workspace, split, speed_value, f"{base_stem}_base", base_mask)
-      written += 1
+      row_written = 0
+      if write_mask(workspace, split, speed_value, f"{base_stem}_base", base_mask):
+        written += 1
+        row_written += 1
 
       for variant_index in range(max(args.variants_per_example, 0)):
         augmented = augment_mask(mask, rng)
-        write_mask(workspace, split, speed_value, f"{base_stem}_var{variant_index:02d}", augmented)
-        written += 1
-      imported += 1
+        if write_mask(workspace, split, speed_value, f"{base_stem}_var{variant_index:02d}", augmented):
+          written += 1
+          row_written += 1
+      if row_written:
+        imported += 1
+      else:
+        skipped_write_failed += 1
     if args.max_rows > 0 and attempted >= args.max_rows:
       break
 
   print(
     "Imported manifest classifier masks: "
     f"attempted={attempted} imported={imported} written={written} "
-    f"skipped_no_speed={skipped_no_speed} skipped_no_crop={skipped_no_crop} skipped_no_mask={skipped_no_mask}"
+    f"skipped_no_speed={skipped_no_speed} skipped_no_crop={skipped_no_crop} skipped_no_mask={skipped_no_mask} "
+    f"skipped_write_failed={skipped_write_failed}"
   )
   return 0
 

scripts/speed_limit_vision/import_manual_review_queue.py

@@ -63,6 +63,7 @@ DETECTOR_MANIFEST_FIELDNAMES = [
 ]
 
 POSITIVE_STATUSES = {"accepted", "corrected"}
+UNCERTAIN_STATUS = "uncertain"
 NEGATIVE_STATUS = "ignore"
 SIGN_TYPE_CLASS_IDS = {
   "regulatory": 0,
@@ -226,6 +227,14 @@ def is_positive(row: dict[str, str]) -> bool:
   return Path(row.get("crop_path", "")).is_file() and Path(row.get("frame_path", "")).is_file()
 
 
+def is_uncertain_positive(row: dict[str, str]) -> bool:
+  if row.get("review_status") != UNCERTAIN_STATUS:
+    return False
+  if not parse_speed(row.get("review_speed_limit_mph", "")):
+    return False
+  return Path(row.get("frame_path", "")).is_file()
+
+
 def is_true_negative(row: dict[str, str]) -> bool:
   if row.get("review_status") != NEGATIVE_STATUS:
     return False
@@ -253,7 +262,7 @@ def positive_classifier_row(row: dict[str, str], split: str) -> dict[str, object
 
 
 def runtime_row(row: dict[str, str], split: str, sample_type: str) -> dict[str, object]:
-  speed = parse_speed(row.get("review_speed_limit_mph", "")) if sample_type == "positive" else 0
+  speed = parse_speed(row.get("review_speed_limit_mph", "")) if sample_type in ("positive", "uncertain_positive") else 0
   return {
     "record_key": row["record_key"],
     "split": split,
@@ -331,6 +340,7 @@ def main() -> int:
 
   rows = merged_review_rows(queue_path, labels_path)
   positive_rows = [row for row in rows if is_positive(row)]
+  uncertain_positive_rows = [row for row in rows if is_uncertain_positive(row)]
   true_negative_rows = [row for row in rows if is_true_negative(row)]
   if args.max_detector_negatives > 0:
     true_negative_rows = true_negative_rows[:args.max_detector_negatives]
@@ -347,6 +357,10 @@ def main() -> int:
     if detector_row is not None:
       detector_rows.append(detector_row)
 
+  for row in uncertain_positive_rows:
+    split = split_for_key(row["record_key"], args.val_modulo, args.val_remainder)
+    runtime_rows.append(runtime_row(row, split, "uncertain_positive"))
+
   for row in true_negative_rows:
     split = split_for_key(row["record_key"], args.val_modulo, args.val_remainder)
     runtime_rows.append(runtime_row(row, split, "negative_empty"))
@@ -363,6 +377,7 @@ def main() -> int:
     "labels": str(labels_path),
     "reviewed_rows": len(rows),
     "positive_rows": len(positive_rows),
+    "uncertain_positive_rows": len(uncertain_positive_rows),
     "true_negative_rows": len(true_negative_rows),
     "classifier_manifest": str(classifier_manifest),
     "runtime_manifest": str(runtime_manifest),
@@ -374,7 +389,7 @@ def main() -> int:
 
   print(
     "Imported manual review queue: "
-    f"reviewed={len(rows)} positives={len(positive_rows)} true_negatives={len(true_negative_rows)} "
+    f"reviewed={len(rows)} positives={len(positive_rows)} uncertain_positives={len(uncertain_positive_rows)} true_negatives={len(true_negative_rows)} "
     f"detector_imported={len(detector_rows)}"
   )
   print(f"Classifier manifest: {classifier_manifest}")

scripts/speed_limit_vision/serve_manual_review_queue.py

@@ -79,7 +79,7 @@ HTML = r"""<!doctype html>
       <option value="negative">Negatives</option>
     </select>
     <span class="status" id="status"></span>
-    <span class="muted">Keys: Space/p accept model, type speed to correct, i/x ignore, Enter save correction, j/k next/prev, s school, r regulatory, a advisory</span>
+    <span class="muted">Keys: Space/p accept model, type speed to correct, u uncertain, i/x ignore, Enter save correction, j/k next/prev, s school, r regulatory, a advisory</span>
   </header>
   <main>
     <section class="images">
@@ -107,6 +107,7 @@ HTML = r"""<!doctype html>
       <h3>Action</h3>
       <div class="buttons" id="statusButtons">
         <button data-status="ignore" class="warn">Ignore / Bad Crop (i/x)</button>
+        <button data-status="uncertain">Uncertain (u)</button>
         <button data-status="needs_later">Needs Later</button>
       </div>
       <label>Box</label>
@@ -356,7 +357,7 @@ function render() {
 }
 
 function manualReviewStatus() {
-  if (draft.review_status === "ignore" || draft.review_status === "needs_later") return draft.review_status;
+  if (draft.review_status === "ignore" || draft.review_status === "needs_later" || draft.review_status === "uncertain") return draft.review_status;
   return "corrected";
 }
 
@@ -440,6 +441,17 @@ document.addEventListener("keydown", ev => {
     save(true, "ignore");
     return;
   }
+  if (key === "u") {
+    clearSpeedBuffer();
+    draft.review_status = "uncertain";
+    if (!draft.review_speed_limit_mph) draft.review_speed_limit_mph = current.candidate_speed_limit_mph || "";
+    ensureSpeedSignType();
+    setActive("#statusButtons button", "status", "uncertain");
+    setActive("#speedButtons button", "speed", draft.review_speed_limit_mph);
+    setActive("#typeButtons button", "type", draft.review_sign_type);
+    save(true, "uncertain");
+    return;
+  }
   if (key === "enter") { clearSpeedBuffer(); save(true); }
 });
 loadQueue();