def week2_adaptive_hsv(video: Video, debug=False) -> Iterator[Frame]:
model_mean, model_std = get_background_model(video,
int(2141 * 0.25),
total_frames=int(2141 * 0.25),
pixel_value=PixelValue.HSV)
ground_truth = read_detections(
'../datasets/AICity_data/train/S03/c010/gt/gt.txt')
frame_id = int(2141 * 0.25)
roi = cv2.cvtColor(
cv2.imread('../datasets/AICity_data/train/S03/c010/roi.jpg'),
cv2.COLOR_BGR2GRAY)
for im, mask in gaussian_model_adaptive(video,
int(2141 * 0.25),
model_mean,
model_std,
total_frames=int(2141 * 0.10),
pixel_value=PixelValue.HSV,
alpha=1.75,
rho=0.01):
mask = mask & roi
if debug:
cv2.imshow('f', mask)
cv2.waitKey()
mask = opening(mask, 7)
if debug:
cv2.imshow('f', mask)
cv2.waitKey()
mask = closing(mask, 35)
if debug:
cv2.imshow('f', mask)
cv2.waitKey()
mask, detections = find_boxes(mask)
frame = Frame(frame_id)
frame.detections = detections
frame.ground_truth = ground_truth[frame_id]
if debug:
mask2 = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
for detection in detections:
cv2.rectangle(
mask2,
(int(detection.top_left[1]), int(detection.top_left[0])),
(int(detection.get_bottom_right()[1]),
int(detection.get_bottom_right()[0])), (0, 255, 0), 5)
for gt in ground_truth[frame_id]:
cv2.rectangle(mask2,
(int(gt.top_left[1]), int(gt.top_left[0])),
(int(gt.get_bottom_right()[1]),
int(gt.get_bottom_right()[0])), (255, 0, 0), 5)
cv2.imshow('f', mask2)
cv2.waitKey()
yield im, mask, frame
frame_id += 1
def week2_soa(video: Video, debug=False) -> Iterator[Frame]:
th = 150
frame_id = 0
fgbg = cv.createBackgroundSubtractorMOG2()
ground_truth = read_detections(
'../datasets/AICity_data/train/S03/c010/gt/gt.txt')
roi = cv.cvtColor(
cv.imread('../datasets/AICity_data/train/S03/c010/roi.jpg'),
cv.COLOR_BGR2GRAY)
for im in tqdm(video.get_frames(),
total=2141,
file=sys.stdout,
desc='Training model...'):
mask = fgbg.apply(im)
mask[mask < th] = 0
mask.astype(np.uint8) * 255
mask = mask & roi
mask = opening(mask, 5)
# cv.imshow('f', mask)
# cv.waitKey()
mask = closing(mask, 25)
# cv.imshow('f', mask)
# cv.waitKey()
mask, detections = find_boxes(mask)
frame = Frame(frame_id)
frame.detections = detections
frame.ground_truth = ground_truth[frame_id]
frame_id += 1
yield im, mask, frame