def visualize(self):
frame = self.frame
# draw and label blob bounding boxes
for _id, blob in self.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) + '(' + str(blob.vehicle_type) + ')',
(x, y - 2), cv2.FONT_HERSHEY_DUPLEX, 1, (0, 255, 0), 2,
cv2.LINE_AA)
# draw counting line
if self.counting_line != None:
cv2.line(frame, self.counting_line[0], self.counting_line[1],
(255, 215, 0), 3)
# display vehicle count
text_org_y = 60
cv2.putText(frame, 'Count: ' + str(self.vehicle_count),
(20, text_org_y), cv2.FONT_HERSHEY_DUPLEX, 1.5,
(0, 0, 255), 2, cv2.LINE_AA)
cv2.putText(frame, 'Cars_count: ' + str(self.car_count),
(20, text_org_y * 2), cv2.FONT_HERSHEY_DUPLEX, 1.5,
(0, 0, 255), 2, cv2.LINE_AA)
cv2.putText(frame, 'Trucks_count: ' + str(self.truck_count),
(20, text_org_y * 3), cv2.FONT_HERSHEY_DUPLEX, 1.5,
(0, 0, 255), 2, cv2.LINE_AA)
cv2.putText(frame, 'Bicycles_count: ' + str(self.bicycle_count),
(20, text_org_y * 4), cv2.FONT_HERSHEY_DUPLEX, 1.5,
(0, 0, 255), 2, cv2.LINE_AA)
# show detection roi
if self.show_droi:
frame = draw_roi(frame, self.droi)
return frame
def visualize(self):
_frame = self.frame
# draw and label blob bounding boxes
for _id, blob in self.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
if self.counting_line is not None:
cv2.line(_frame, self.counting_line[0], self.counting_line[1], (0, 255, 0), 3)
# display vehicle count
cv2.putText(_frame, 'Count: ' + str(self.vehicle_count), (20, 60), cv2.FONT_HERSHEY_DUPLEX, 2, (255, 0, 0), 2,
cv2.LINE_AA)
# show detection roi
if self.show_droi:
_frame = draw_roi(_frame, self.droi)
return _frame
(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)
# 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)
# save frame in video output
if args.record:
output_video.write(frame)
# visualize vehicle counting
if not args.hideimage:
resized_frame = cv2.resize(frame, (858, 480))
cv2.imshow('tracking', resized_frame)
frame_counter += 1
# save frame if 's' key is pressed
if k & 0xFF == ord('s'):
cv2.imwrite(
def visualize(self):
ha = os.path.join('detect-and-count-object','detectors')
path = os.path.join(ha,'yolo')
labelsPath = os.path.join(path,'coco.names')
LABELS = open(labelsPath).read().strip().split("\n")
# initialize a list of colors to represent each possible class label
np.random.seed(42)
COLORS = np.random.randint(0, 255, size=(len(LABELS), 3),
dtype="uint8")
frame = self.frame
f_height, f_width, _ = frame.shape
# draw and label blob bounding boxes
droi_frame = get_roi_frame(self.frame, self.droi)
boxes = get_bounding_boxes(droi_frame, self.detector)
if self.detector == 'yolo':
for box in boxes:
boxs = box[0]
for i in box[2].flatten():
(x, y) = (int(boxs[0]), int(boxs[1]))
(w, h) = (int(boxs[2]), int(boxs[3]))
color = [int(c) for c in COLORS[box[1][0]]]
cv2.rectangle(frame, (x, y), (x + w, y + h), color, 2)
text = "{}: {:.4f}".format(LABELS[box[1][0]],box[1][1])
cv2.putText(frame, text, (x, y - 5),cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
else:
for _id, blob in self.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, self.counting_line[0], self.counting_line[1], (0, 255, 0), 3)
# display vehicle count
cv2.rectangle(frame, (0, 0), (f_width, 75), (180, 132, 109), -1)
textPosition = int(f_width/7)
if f_width <= 1280:
textSize = 0.5
else:
textSize = 1
cv2.putText(frame, 'Total: ' + str(self.vehicle_count), (10, 60), cv2.FONT_HERSHEY_DUPLEX, textSize, (255, 0, 0,), 1, cv2.LINE_AA)
cv2.putText(frame, 'Car: ' + str(self.countCar), (textPosition, 60), cv2.FONT_HERSHEY_DUPLEX, textSize, (255, 0, 0), 1, cv2.LINE_AA)
cv2.putText(frame, 'Bus: ' + str(self.countBus), (textPosition*2, 60), cv2.FONT_HERSHEY_DUPLEX, textSize, (255, 0, 0), 1, cv2.LINE_AA)
cv2.putText(frame, 'Truck: ' + str(self.countTruck), (textPosition*3, 60), cv2.FONT_HERSHEY_DUPLEX, textSize, (255, 0, 0), 1, cv2.LINE_AA)
cv2.putText(frame, 'People: ' + str(self.countPerson), (textPosition*4, 60), cv2.FONT_HERSHEY_DUPLEX, textSize, (255, 0, 0), 1, cv2.LINE_AA)
cv2.putText(frame, 'Bicycle: ' + str(self.countBicycle), (textPosition*5, 60), cv2.FONT_HERSHEY_DUPLEX, textSize, (255, 0, 0), 1, cv2.LINE_AA)
cv2.putText(frame, 'Motorcycle: ' + str(self.countMotorcycle), (textPosition*6, 60), cv2.FONT_HERSHEY_DUPLEX, textSize, (255, 0, 0), 1, cv2.LINE_AA)
# show detection roi
if self.show_droi:
frame = draw_roi(frame, self.droi)
return frame
def count(self, frame):
log = []
self.frame = frame
# initialize a list of colors to represent each possible class label
np.random.seed(42)
COLORS = np.random.randint(0, 255, size=(200, 3), dtype="uint8")
droi_frame = get_roi_frame(self.frame, self.droi)
dets = get_bounding_boxes(droi_frame, detection_type)
np.set_printoptions(
formatter={'float': lambda x: "{0:0.3f}".format(x)})
dets = np.asarray(dets)
tracks = self.tracker.update(dets)
boxes = []
indexIDs = []
classIDs = []
c = []
previous = self.memory.copy()
self.memory = {}
for track in tracks:
boxes.append([track[0], track[1], track[2], track[3]])
indexIDs.append(int(track[4]))
classIDs.append(int(track[5]))
self.memory[indexIDs[-1]] = boxes[-1]
if len(boxes) > 0:
i = int(0)
for box in boxes:
# extract the bounding box coordinates
(x, y) = (int(box[0]), int(box[1]))
(w, h) = (int(box[2]), int(box[3]))
color = [int(c) for c in COLORS[indexIDs[i] % len(COLORS)]]
cv2.rectangle(self.frame, (x, y), (w, h), color, 2)
if indexIDs[i] in previous:
previous_box = previous[indexIDs[i]]
(x2, y2) = (int(previous_box[0]), int(previous_box[1]))
(w2, h2) = (int(previous_box[2]), int(previous_box[3]))
p0 = (int(x + (w - x) / 2), int(y + (h - y) / 2))
p1 = (int(x2 + (w2 - x2) / 2), int(y2 + (h2 - y2) / 2))
cv2.line(self.frame, p0, p1, color, 3)
if intersect(p0, p1, self.red_line[0], self.red_line[1]):
self.vehicle_count += 1
log.append({
'blob_id': indexIDs[i],
'type': get_class_name(classIDs[i]),
'count': self.vehicle_count,
'datetime': datetime.now()
})
# text = "{}: {:.4f}".format(LABELS[classIDs[i]], confidences[i])
text = "{}-{}".format(get_class_name(classIDs[i]), indexIDs[i])
cv2.putText(self.frame, text, (x, y - 5),
cv2.FONT_HERSHEY_SIMPLEX, 1, color, 2)
i += 1
# draw line
cv2.line(self.frame, self.red_line[0], self.red_line[1], (0, 0, 255),
5)
# draw counter
cv2.putText(self.frame, str(self.vehicle_count), (100, 200),
cv2.FONT_HERSHEY_DUPLEX, 5.0, (0, 255, 0), 10)
self.frame = draw_roi(self.frame, self.droi)
return log, self.frame