frame_counter = 0
DETECTION_FRAME_RATE = 48
term_criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1)
def create_blob(_box):
x, y, w, h = [int(v) for v in _box]
roi = frame[y:y + h, x:x + w]
hsv_roi = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
roi_hist = cv2.calcHist([hsv_roi], [0], None, [180], [0, 180])
return Blob((x, y, w, h), roi_hist)
# initialize trackers and create new blobs
_, frame = cap.read()
initial_bboxes = get_bounding_boxes(frame)
for box in initial_bboxes:
_blob = create_blob(box)
blobs[blob_id] = _blob
while True:
if cap.get(cv2.CAP_PROP_POS_FRAMES) + 1 < cap.get(
cv2.CAP_PROP_FRAME_COUNT):
_, frame = cap.read()
output_frame = frame.copy()
# update camshift tracker
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
for _id, blob in list(blobs.items()):
mask = cv2.calcBackProject([hsv], [0], blob.roi_hist, [0, 180], 1)
ret, _ = cv2.CamShift(mask, blob.roi_box, term_criteria)
cl_y = round(4 / 5 * f_height)
counting_line = [(0, cl_y), (f_width, cl_y)]
vehicle_count = 0
# create detection ROI
droi = [(0, 0), (f_width, 0), (f_width, f_height), (0, f_height)]
if args.droi:
droi = []
points = args.droi.replace(' ', '').split('|')
for point_str in points:
point = tuple(map(int, point_str.split(',')))
droi.append(point)
# initialize trackers and create new blobs
droi_frame = get_roi_frame(frame, droi)
initial_bboxes = get_bounding_boxes(droi_frame)
for box in initial_bboxes:
tracker = cv2.TrackerCSRT_create()
tracker.init(frame, tuple(box))
_blob = Blob(box, tracker)
blobs[blob_id] = _blob
while True:
k = cv2.waitKey(1)
if cap.get(cv2.CAP_PROP_POS_FRAMES) + 1 < cap.get(cv2.CAP_PROP_FRAME_COUNT):
_, frame = cap.read()
for _id, blob in list(blobs.items()):
# update trackers
success, box = blob.tracker.update(frame)
if success: