def __init__(self, initial_frame, detector, tracker, droi, show_droi, mcdf,
mctf, di, cl_position):
self.frame = initial_frame # current frame of video
self.detector = detector
self.tracker = tracker
self.droi = droi # detection region of interest
self.show_droi = show_droi
self.mcdf = mcdf # maximum consecutive detection failures
self.mctf = mctf # maximum consecutive tracking failures
self.di = di # detection interval
self.cl_position = cl_position # counting line position
self.blobs = OrderedDict()
self.f_height, self.f_width, _ = self.frame.shape
self.frame_count = 0 # number of frames since last detection
self.vehicle_count = 0 # number of vehicles counted
self.types_counts = OrderedDict() # counts by vehicle type
self.counting_line = None if cl_position == None else get_counting_line(
self.cl_position, self.f_width, self.f_height)
# create blobs from initial frame
droi_frame = get_roi_frame(self.frame, self.droi)
_bounding_boxes, _classes, _confidences = get_bounding_boxes(
droi_frame, self.detector)
#print (droi_frame)
self.blobs = add_new_blobs(_bounding_boxes, _classes, _confidences,
self.blobs, self.frame, self.tracker,
self.counting_line, self.cl_position,
self.mcdf)
def count(self, frame):
log = []
self.frame = frame
for _id, blob in list(self.blobs.items()):
# update trackers
success, box = blob.tracker.update(self.frame)
if success:
blob.num_consecutive_tracking_failures = 0
blob.update(box)
else:
blob.num_consecutive_tracking_failures += 1
# count vehicles that have left the frame if no counting line exists
# or those that have passed the counting line if one exists
if (self.counting_line == None and
(blob.num_consecutive_tracking_failures == self.mctf or blob.num_consecutive_detection_failures == self.mcdf) and
not blob.counted) \
or \
(self.counting_line != None and
is_passed_counting_line(blob.centroid, self.counting_line, self.cl_position) and
not blob.counted):
blob.counted = True
self.vehicle_count += 1
# classes_of_interest = ['bicycle', 'car', 'motorcycle', 'bus', 'truck', 'person']
if blob.vehicle_type == 'bicycle':
self.bicycle_count += 1
elif blob.vehicle_type == 'car':
self.car_count += 1
elif blob.vehicle_type == 'truck':
self.truck_count += 1
elif blob.vehicle_type == 'bus':
self.bus_count += 1
log.append({
'blob_id': _id,
'count': self.vehicle_count,
'datetime': datetime.now()
})
if blob.num_consecutive_tracking_failures >= self.mctf:
# delete untracked blobs
del self.blobs[_id]
if self.frame_count >= self.di:
# rerun detection
droi_frame = get_roi_frame(self.frame, self.droi)
boxes, classes_types = get_bounding_boxes(droi_frame,
self.detector)
self.blobs, current_blob_id = add_new_blobs(
boxes, classes_types, self.blobs, self.frame, self.tracker,
self.blob_id, self.counting_line, self.cl_position, self.mcdf)
self.blob_id = current_blob_id
self.blobs = remove_duplicates(self.blobs)
self.frame_count = 0
self.frame_count += 1
return log
def count(self, frame):
log = []
self.frame = frame
if self.frame_count >= self.di:
# rerun detection
droi_frame = get_roi_frame(self.frame, self.droi)
boxes = get_bounding_boxes(droi_frame, self.detector)
self.blobs, current_blob_id = add_new_blobs(
boxes, self.blobs, self.frame, self.tracker, self.blob_id,
self.counting_line, self.cl_position, self.mcdf)
self.blob_id = current_blob_id
self.blobs = remove_duplicates(self.blobs)
self.frame_count = 0
for _id, blob in list(self.blobs.items()):
# update trackers
success, box = blob.tracker.update(self.frame)
if success:
blob.num_consecutive_tracking_failures = 0
blob.update(box)
else:
blob.num_consecutive_tracking_failures += 1
# delete untracked blobs
if blob.num_consecutive_tracking_failures >= self.mctf:
del self.blobs[_id]
# count vehicles
if is_passed_counting_line(blob.centroid, self.counting_line,
self.cl_position) and not blob.counted:
blob.counted = True
self.vehicle_count += 1
(x, y, w, h) = [int(v) for v in blob.bounding_box]
roi = self.frame[y:y + h + 40, x:x + w + 40]
#cv2.imwrite(f"./detected/{self.vehicle_count}.jpg", roi)
cv2.imwrite("./roi.jpg", roi)
log.append({
'blob_id': _id,
'count': self.vehicle_count,
'datetime': datetime.now()
})
self.frame_count += 1
return log
vehicle_count += 1
# log count data to a file (vehicle_id, count, datetime)
if args.record:
_row = '{0}, {1}, {2}\n'.format('v_' + str(_id),
vehicle_count,
datetime.now())
log_file.write(_row)
log_file.flush()
if frame_counter >= DETECTION_INTERVAL:
# rerun detection
droi_frame = get_roi_frame(frame, droi)
boxes = get_bounding_boxes(droi_frame, detector)
blobs, current_blob_id = add_new_blobs(boxes, blobs, frame,
tracker, blob_id,
counting_line, clposition)
blob_id = current_blob_id
blobs = remove_duplicates(blobs)
frame_counter = 0
# draw and label blob bounding boxes
for _id, blob in blobs.items():
(x, y, w, h) = [int(v) for v in blob.bounding_box]
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(frame, 'v_' + str(_id), (x, y - 2),
cv2.FONT_HERSHEY_DUPLEX, 1, (0, 255, 0), 2,
cv2.LINE_AA)
# draw counting line
cv2.line(frame, counting_line[0], counting_line[1], (0, 255, 0), 3)
def count(self, frame):
log = []
self.frame = frame
for _id, blob in list(self.blobs.items()):
# update trackers
success, box = blob.tracker.update(self.frame)
if success:
blob.num_consecutive_tracking_failures = 0
blob.update(box)
log_info(
'Vehicle tracker updated.', {
'event': 'TRACKER_UPDATE',
'vehicle_id': _id,
'bounding_box': blob.bounding_box,
'centroid': blob.centroid,
})
f = './ProcessRecords/Vehicletrackerupdated58.txt'
with open(f, "a") as file:
file.write('TRACKER_UPDATE' + '-' + 'id' + str(_id) + '-' +
'bounding_box' + str(blob.bounding_box) + '-' +
'centroid' + str(blob.centroid) + "\n")
else:
blob.num_consecutive_tracking_failures += 1
# count vehicles that have left the frame if no counting line exists
# or those that have passed the counting line if one exists
if (self.counting_line == None and \
(blob.num_consecutive_tracking_failures == self.mctf or blob.num_consecutive_detection_failures == self.mcdf) and \
not blob.counted) \
or \
(self.counting_line != None and \
# don't count a blob if it was first detected at a position past the counting line
# this enforces counting in only one direction
not is_passed_counting_line(blob.position_first_detected, self.counting_line, self.cl_position) and \
is_passed_counting_line(blob.centroid, self.counting_line, self.cl_position) and \
not blob.counted):
blob.counted = True
self.vehicle_count += 1
# count by vehicle type
if blob.type != None:
if blob.type in self.types_counts:
self.types_counts[blob.type] += 1
else:
self.types_counts[blob.type] = 1
log_info(
'Vehicle counted.', {
'event': 'VEHICLE_COUNT',
'id': _id,
'type': blob.type,
'count': self.vehicle_count,
'position_first_detected':
blob.position_first_detected,
'position_counted': blob.centroid,
'counted_at': time.time(),
})
f = './ProcessRecords/Vehiclecounted58.txt'
with open(f, "a") as file:
file.write('VEHICLE_COUNT' + '-' + 'id' + str(_id) + '-' +
'type' + str(blob.type) + '-' + 'count' +
str(self.vehicle_count) + '-' +
'position_first_detected' +
str(blob.position_first_detected) + '-' +
'position_counted' + str(blob.centroid) + '-' +
'counted_at' + str(time.time()) + "\n")
if blob.num_consecutive_tracking_failures >= self.mctf:
# delete untracked blobs
del self.blobs[_id]
if self.frame_count >= self.di:
# rerun detection
droi_frame = get_roi_frame(self.frame, self.droi)
_bounding_boxes, _classes, _confidences = get_bounding_boxes(
droi_frame, self.detector)
self.blobs = add_new_blobs(_bounding_boxes, _classes, _confidences,
self.blobs, self.frame, self.tracker,
self.counting_line, self.cl_position,
self.mcdf)
self.blobs = remove_duplicates(self.blobs)
self.frame_count = 0
self.frame_count += 1
return log
def count(self, frame):
log = []
self.frame = frame
if self.frame_count >= self.di:
# rerun detection
droi_frame = get_roi_frame(self.frame, self.droi)
boxes = get_bounding_boxes(droi_frame, self.detector)
#print(self.blobs)
self.blobs, current_blob_id = add_new_blobs(boxes, self.blobs, self.frame, self.tracker, self.blob_id, self.counting_line, self.cl_position, self.mcdf, self.detector)
self.blob_id = current_blob_id
self.blobs = remove_duplicates(self.blobs)
self.frame_count = 0
for _id, blob in list(self.blobs.items()):
# update trackers
#print(blob[0])
success, box = blob[0].tracker.update(self.frame)
if success:
blob[0].num_consecutive_tracking_failures = 0
blob[0].update(box)
else:
blob[0].num_consecutive_tracking_failures += 1
# delete untracked blobs
if blob[0].num_consecutive_tracking_failures >= self.mctf:
del self.blobs[_id]
# count vehicles
if is_passed_counting_line(blob[0].centroid, self.counting_line, self.cl_position) and not blob[0].counted:
blob[0].counted = True
if blob[1] == 'car':
self.countCar +=1
elif blob[1] == 'bus':
self.countBus +=1
elif blob[1] == 'truck':
self.countTruck +=1
elif blob[1] == 'person':
self.countPerson +=1
elif blob[1] == 'bicycle':
self.countBicycle +=1
elif blob[1] == 'motorcycle':
self.countMotorcycle +=1
self.vehicle_count += 1
log.append({'blob_id': _id, 'count': self.vehicle_count, 'datetime': datetime.now()})
self.frame_count += 1
return log
# count vehicles
if blob.centroid[1] >= cl_y and not blob.counted:
blob.counted = True
vehicle_count += 1
# log count data to a file (vehicle_id, count, datetime)
_row = '{0}, {1}, {2}\n'.format('v_' + str(_id), vehicle_count, datetime.now())
log_file.write(_row)
log_file.flush()
if frame_counter >= DETECTION_INTERVAL:
# rerun detection
droi_frame = get_roi_frame(frame, droi)
boxes = get_bounding_boxes(droi_frame, detector)
blobs, current_blob_id = add_new_blobs(boxes, blobs, frame, tracker, blob_id)
blob_id = current_blob_id
blobs = remove_duplicates(blobs)
frame_counter = 0
# draw counting line
cv2.line(frame, counting_line[0], counting_line[1], (0, 255, 0), 3)
# display vehicle count
cv2.putText(frame, 'Count: ' + str(vehicle_count), (20, 60), cv2.FONT_HERSHEY_DUPLEX, 2, (255, 0, 0), 2, cv2.LINE_AA)
# show detection roi
if args.showdroi:
frame = draw_roi(frame, droi)
# visualize vehicle counting
