Remove all fallbacks: show errors, draw debug lines on calibration
- Remove try-except in CameraCalibrator — errors propagate to UI - Remove auto-load of saved calibrations — always start uncalibrated - Remove hardcoded "Base Setup" card with fake values - Remove addStereocameras/getCamParams dead code - Draw all detected Hough lines + corners on debug frame during calibration - Show debug images in calibration tab after attempt - Show error messages in UI instead of swallowing them Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Ruslan Bakiev
158
jetson/main.py
158
jetson/main.py
@@ -39,11 +39,9 @@ def auto_calibrate():
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compute camera pose, save to config.
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Each camera sees one half of the court from the net position.
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We use the court lines visible in each frame to build correspondences.
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For now: use a simple approach — detect the 4 most prominent lines
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(baseline, two sidelines, kitchen line) and map to known 3D coords.
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Returns error if court lines cannot be detected (no fallbacks).
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Detects court lines via Hough transform, finds 4 corners,
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then uses solvePnP to determine camera position.
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Returns debug images with detected lines drawn on them.
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"""
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results = {}
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@@ -55,51 +53,93 @@ def auto_calibrate():
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h, w = frame.shape[:2]
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side = 'left' if sensor_id == 0 else 'right'
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debug_frame = frame.copy()
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# Try to detect court lines using edge detection + Hough
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corners_pixel = _detect_court_corners(frame, side)
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# Detect court lines — returns corners + debug info
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detection = _detect_court_corners(frame, side)
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# Draw all detected Hough lines on debug frame
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if detection and detection.get('all_lines') is not None:
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for line in detection['all_lines']:
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x1, y1, x2, y2 = line[0]
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cv2.line(debug_frame, (x1, y1), (x2, y2), (50, 50, 50), 1)
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# Draw classified lines
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if detection and detection.get('horizontals'):
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for line in detection['horizontals']:
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x1, y1, x2, y2 = line
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cv2.line(debug_frame, (x1, y1), (x2, y2), (0, 255, 255), 2) # yellow = horizontal
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if detection and detection.get('verticals'):
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for line in detection['verticals']:
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x1, y1, x2, y2 = line
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cv2.line(debug_frame, (x1, y1), (x2, y2), (255, 0, 255), 2) # magenta = vertical
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# Draw selected 4 lines (top/bottom/left/right)
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if detection and detection.get('selected_lines'):
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sel = detection['selected_lines']
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colors = {'top': (0, 255, 0), 'bottom': (0, 200, 0),
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'left': (255, 128, 0), 'right': (200, 100, 0)}
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for name, line in sel.items():
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x1, y1, x2, y2 = line
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cv2.line(debug_frame, (x1, y1), (x2, y2), colors.get(name, (255, 255, 255)), 3)
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cv2.putText(debug_frame, name, (x1, y1 - 5),
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cv2.FONT_HERSHEY_SIMPLEX, 0.5, colors.get(name, (255, 255, 255)), 1)
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# Encode debug frame
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_, jpeg = cv2.imencode('.jpg', debug_frame, [cv2.IMWRITE_JPEG_QUALITY, 85])
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debug_b64 = base64.b64encode(jpeg.tobytes()).decode('ascii')
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corners_pixel = detection.get('corners') if detection else None
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if corners_pixel is None:
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error_detail = detection.get('error', 'Unknown') if detection else 'No lines detected at all'
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results[str(sensor_id)] = {
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'ok': False,
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'error': f'Could not detect court lines for CAM {sensor_id}. '
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'Ensure court lines are clearly visible.'
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'error': f'CAM {sensor_id}: {error_detail}',
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'debug_image': debug_b64,
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}
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continue
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# Draw corners on debug frame
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for i, corner in enumerate(corners_pixel):
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pt = (int(corner[0]), int(corner[1]))
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cv2.circle(debug_frame, pt, 8, (0, 0, 255), -1)
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cv2.putText(debug_frame, f'C{i}', (pt[0] + 10, pt[1]),
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cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
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# Re-encode with corners
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_, jpeg = cv2.imencode('.jpg', debug_frame, [cv2.IMWRITE_JPEG_QUALITY, 85])
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debug_b64 = base64.b64encode(jpeg.tobytes()).decode('ascii')
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# Get known 3D coordinates for this half
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corners_3d = get_half_court_3d_points(side)
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# Calibrate
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# Calibrate — no try/except, let errors propagate
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cal = CameraCalibrator()
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ok = cal.calibrate(
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cal.calibrate(
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np.array(corners_pixel, dtype=np.float32),
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corners_3d,
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w, h
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)
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if ok:
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# Save to config
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cal_path = os.path.join(_args.calibration_dir,
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f'cam{sensor_id}_calibration.json')
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os.makedirs(os.path.dirname(cal_path), exist_ok=True)
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cal.save(cal_path)
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# Save to config
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cal_path = os.path.join(_args.calibration_dir,
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f'cam{sensor_id}_calibration.json')
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os.makedirs(os.path.dirname(cal_path), exist_ok=True)
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cal.save(cal_path)
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state['calibrators'][sensor_id] = cal
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state['calibrators'][sensor_id] = cal
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# Get camera position for 3D scene
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cam_pos = (-cal.rotation_matrix.T @ cal.translation_vec).flatten()
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# Get camera position for 3D scene
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cam_pos = (-cal.rotation_matrix.T @ cal.translation_vec).flatten()
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results[str(sensor_id)] = {
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'ok': True,
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'camera_position': cam_pos.tolist(),
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'corners_pixel': corners_pixel.tolist() if isinstance(corners_pixel, np.ndarray)
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else corners_pixel,
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}
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print(f"[CAM {sensor_id}] Calibrated! Camera at "
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f"({cam_pos[0]:.1f}, {cam_pos[1]:.1f}, {cam_pos[2]:.1f})")
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else:
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results[str(sensor_id)] = {'ok': False, 'error': 'Calibration failed'}
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results[str(sensor_id)] = {
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'ok': True,
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'camera_position': cam_pos.tolist(),
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'debug_image': debug_b64,
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}
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print(f"[CAM {sensor_id}] Calibrated! Camera at "
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f"({cam_pos[0]:.1f}, {cam_pos[1]:.1f}, {cam_pos[2]:.1f})")
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return results
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@@ -107,7 +147,13 @@ def auto_calibrate():
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def _detect_court_corners(frame, side):
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"""Detect court corners from frame using edge detection.
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Returns 4 corner points as numpy array, or None if detection fails.
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Returns dict with:
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corners: 4x2 numpy array or None
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all_lines: raw Hough lines
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horizontals: classified horizontal lines
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verticals: classified vertical lines
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selected_lines: the 4 lines used (top/bottom/left/right)
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error: description if detection failed
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"""
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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blur = cv2.GaussianBlur(gray, (5, 5), 0)
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@@ -118,7 +164,13 @@ def _detect_court_corners(frame, side):
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minLineLength=100, maxLineGap=20)
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if lines is None or len(lines) < 4:
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return None
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n = 0 if lines is None else len(lines)
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return {
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'corners': None, 'all_lines': lines,
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'horizontals': [], 'verticals': [],
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'selected_lines': {},
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'error': f'Only {n} Hough lines found (need >= 4)',
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}
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# Classify lines into horizontal and vertical
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horizontals = []
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@@ -134,20 +186,28 @@ def _detect_court_corners(frame, side):
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verticals.append(line[0])
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if len(horizontals) < 2 or len(verticals) < 2:
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return None
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return {
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'corners': None, 'all_lines': lines,
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'horizontals': [h.tolist() for h in horizontals],
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'verticals': [v.tolist() for v in verticals],
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'selected_lines': {},
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'error': f'{len(horizontals)} horizontal, {len(verticals)} vertical lines (need >= 2 each)',
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}
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# Cluster lines by position to find the dominant ones
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h_positions = sorted(horizontals, key=lambda l: (l[1] + l[3]) / 2)
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v_positions = sorted(verticals, key=lambda l: (l[0] + l[2]) / 2)
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# Take the most separated horizontal pair (top and bottom court lines)
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top_line = h_positions[0]
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bottom_line = h_positions[-1]
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# Take the most separated vertical pair (left and right sidelines)
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left_line = v_positions[0]
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right_line = v_positions[-1]
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selected = {
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'top': top_line.tolist(), 'bottom': bottom_line.tolist(),
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'left': left_line.tolist(), 'right': right_line.tolist(),
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}
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# Find intersections as corner points
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def line_intersection(l1, l2):
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x1, y1, x2, y2 = l1
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@@ -168,9 +228,22 @@ def _detect_court_corners(frame, side):
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]
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if any(c is None for c in corners):
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return None
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return {
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'corners': None, 'all_lines': lines,
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'horizontals': [h.tolist() for h in horizontals],
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'verticals': [v.tolist() for v in verticals],
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'selected_lines': selected,
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'error': 'Lines are parallel — could not find all 4 corner intersections',
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}
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return np.array(corners, dtype=np.float32)
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return {
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'corners': np.array(corners, dtype=np.float32),
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'all_lines': lines,
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'horizontals': [h.tolist() for h in horizontals],
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'verticals': [v.tolist() for v in verticals],
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'selected_lines': selected,
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'error': None,
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}
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@@ -324,15 +397,10 @@ def main():
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ring_buffer = FrameRingBuffer(max_seconds=args.buffer_seconds, fps=args.fps)
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# Load calibrations if available
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# Start with empty calibrators — user must calibrate via UI
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os.makedirs(args.calibration_dir, exist_ok=True)
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for sensor_id in [0, 1]:
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cal = CameraCalibrator()
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cal_path = os.path.join(args.calibration_dir, f'cam{sensor_id}_calibration.json')
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if os.path.exists(cal_path):
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if cal.load(cal_path):
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print(f"[CAM {sensor_id}] Loaded calibration from {cal_path}")
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state['calibrators'][sensor_id] = cal
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state['calibrators'][sensor_id] = CameraCalibrator()
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# Start camera readers
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cam_readers = {}
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