def analyze(self, video_path, output_video_path, user_id):
# Create opencv video capture object
cap = cv2.VideoCapture(video_path)
writer = None
# Variables initialization
skip_frame_count = 0
track_colors = [(255, 0, 0), (0, 255, 0), (0, 0, 255), (255, 255, 0),
(0, 255, 255), (255, 0, 255), (255, 127, 255),
(127, 0, 255), (127, 0, 127)]
tracks_dictionary = {}
frame_count = 0
# Infinite loop to process video frames
while (True):
# Capture frame-by-frame
ret, frame = cap.read()
if frame is None:
break
# necessary to create dictionary
frame_count += 1
# Make copy of original frame
orig_frame = copy.copy(frame)
# ???????????
# Skip initial frames that display logo
if (skip_frame_count < 15):
skip_frame_count += 1
continue
# Detect and return centeroids of the objects in the frame
centers = self.object_detector.detect(frame)
# If centroids are detected then track them
if (len(centers) > 0):
# Track object using Kalman Filter
self.object_tracker.update(centers)
# For identified object tracks draw tracking line
# Use various colors to indicate different track_id
for i in range(len(self.object_tracker.tracks)):
# check if track is in my dictionary or need to add it
if self.object_tracker.tracks[i].track_id not in tracks_dictionary:
tracks_dictionary[self.object_tracker.tracks[i].track_id] = {}
if (len(self.object_tracker.tracks[i].trace) > 1):
# Add frame and coordinates this track on this frame
# For Unscented Kalman Filter
tracks_dictionary[self.object_tracker.tracks[i].track_id][frame_count] = [
self.object_tracker.tracks[i].trace[len(self.object_tracker.tracks[i].trace) - 1][0],
self.object_tracker.tracks[i].trace[len(self.object_tracker.tracks[i].trace) - 1][1]]
for j in range(len(self.object_tracker.tracks[i].trace) - 1, 1, -1):
# For Unscented Kalman Filter
x1 = self.object_tracker.tracks[i].trace[j][0]
y1 = self.object_tracker.tracks[i].trace[j][1]
x2 = self.object_tracker.tracks[i].trace[j - 1][0]
y2 = self.object_tracker.tracks[i].trace[j - 1][1]
clr = self.object_tracker.tracks[i].track_id % 9
cv2.line(frame, (int(x1), int(y1)), (int(x2), int(y2)), track_colors[clr], 2)
text = "{}".format(self.object_tracker.tracks[i].track_id)
cv2.putText(frame, text, (int(self.object_tracker.tracks[i].trace[len(self.object_tracker.tracks[i].trace) - 1][0]),
int(self.object_tracker.tracks[i].trace[len(self.object_tracker.tracks[i].trace) - 1][
1] + 5)), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
frame = cv2.resize(frame, (1250, 750))
cv2.imshow('Tracking', frame)
# check if the video writer is None
if writer is None:
# initialize our video writer
fourcc = cv2.VideoWriter_fourcc(*"MJPG")
writer = cv2.VideoWriter(output_video_path, fourcc, 30, (frame.shape[1], frame.shape[0]),
True)
# write the output frame to disk
writer.write(frame)
#cv2.waitKey(50)
# Check for key strokes
#k = cv2.waitKey(50) & 0xff
#if k == 27: # 'esc' key has been pressed, exit program.
# break
#if k == 112: # 'p' has been pressed. this will pause/resume the code.
# pause = not pause
# if (pause is True):
# print("Code is paused. Press 'p' to resume..")
# while (pause is True):
# # stay in this loop until
# key = cv2.waitKey(30) & 0xff
# if key == 112:
# pause = False
# print("Resume code..!!")
# break
graphic_builder = GraphicBuilder(tracks_dictionary)
graphic_builder.build()
finish_video_processing_event = FinishVideoProcessingEvent(output_video_path, graphic_builder.tracks_dictionary, graphic_builder.imagePaths, user_id)
event_bus = EventBus(finish_video_processing_event)
event_bus.publish()
cap.release()
writer.release()
cv2.destroyAllWindows()
def upload_image(user_id, option):
if request.method == "POST":
if request.files:
video = request.files["video"]
if video.filename == "":
print("No filename")
return redirect(request.url)
if allowed_video(video.filename):
filename = secure_filename(video.filename)
video.save(
os.path.join(
"C:\\Users\\Алёша\\source\\repos\\VehiclesDataCollection\\ClientAngular\\src\\assets\\",
filename))
#video.save(os.path.join("D:\\StealLog\\", filename))
#option = request.form["option"]
#if bool(option) == True:
#drawing = DrawingMode()
# need to transfer this points like limitation for smth
#drawing.draw("C:\\Users\\Алёша\\source\\repos\\VehiclesDataCollection\\ClientAngular\\src\\assets\\" + filename)
start_video_processing_event = StartVideoProcessingEvent(user_id)
#body = json.dumps(start_video_processing_event.__dict__)
#connection = pika.BlockingConnection(pika.ConnectionParameters('localhost'))
#channel = connection.channel()
#print(type(self.event))
#channel.queue_declare(queue='StartVideoProcessingEvent', durable=True)
#channel.basic_publish(exchange='',
# routing_key='StartVideoProcessingEvent',
# body=body)
#connection.close()
event_bus = EventBus(start_video_processing_event)
event_bus.publish()
# start analyze stage
args_parser = ArgsParser()
args_parser.parse()
# Create Object Detector
detector_factory = DetectorFactory()
object_detector = detector_factory.create_detector(
'yolo', args_parser)
# Create Object Tracker
object_tracker = Tracker(100, 5, 5)
analyzer = Analyzer(object_detector, object_tracker)
# analyzer.analyze('videos/test_occlusion_short_1second.mp4', 'output/readyForRabbit.avi', user_id)
analyzer.analyze(
"C:\\Users\\Алёша\\source\\repos\\VehiclesDataCollection\\ClientAngular\\src\\assets\\"
+ filename,
"C:\\Users\\Алёша\\source\\repos\\VehiclesDataCollection\\ClientAngular\\src\\assets\\output\\"
+ filename, user_id)
print("Video saved")
else:
print("That file extension is not allowed")
return redirect(request.url)
return "OK"
