async def _analyze(self, camera: Camera,
buffer: FrameBuffer) -> MotionDetectionResult:
packet = buffer.get_latest_keyframe()
if packet == None:
return MotionDetectionResult(False, 0, camera)
frames = packet.decode()
vfs = [x for x in frames if isinstance(x, av.VideoFrame)]
if len(vfs) == 0:
return MotionDetectionResult(False, 0, camera)
frame = vfs[0]
img = cv2.cvtColor(frame.to_rgb().to_ndarray(), cv2.COLOR_BGR2RGB)
hog = cv2.HOGDescriptor()
hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())
bounding_boxes, weights = hog.detectMultiScale(img, winStride=(8, 8))
if len(bounding_boxes) == 0:
return MotionDetectionResult(False, 0, camera)
#boxes = []
#for (x, y, w, h) in bounding_boxes:
# boxes.append((x,y,w,h))
#cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
#cv2.imwrite("./recordings/res" + str(self.count) + ".png", img)
#self.count += 1
return MotionDetectionResult(
True, 50, camera,
[[int(x), int(y), int(w), int(h)]
for (x, y, w, h) in bounding_boxes])
async def _analyze(self, camera: Camera,
buffer: FrameBuffer) -> MotionDetectionResult:
packet = buffer.get_latest_keyframe()
if packet == None:
return MotionDetectionResult(False, 0, camera)
frames = packet.decode()
vfs = [x for x in frames if isinstance(x, av.VideoFrame)]
if len(vfs) == 0:
return MotionDetectionResult(False, 0, camera)
frame = vfs[0]
img = cv2.cvtColor(frame.to_rgb().to_ndarray(), cv2.COLOR_BGR2RGB)
img = imutils.resize(img, width=600)
# Resize to have a width of 500px. Improves speed without sacrificing accuracy
if self.initial_frame is None:
self.initial_frame = img
return MotionDetectionResult(False, 0, camera)
dilated_frame = self.backSub.apply(img)
# Find the contours of the dilated version of the thresholded image
contours = cv2.findContours(dilated_frame.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
contours = imutils.grab_contours(contours)
for contour in contours:
boxes = []
# If contour is smaller than the minimum specified area it does not represent
# significant motion and should thus be ignored
if cv2.contourArea(contour) > 500:
return MotionDetectionResult(True, 500, camera, boxes)
return MotionDetectionResult(False, 0, camera)