def test_video_frame_from_bgr(self):
image = numpy.full((480, 640, 3), (0, 0, 0), numpy.uint8)
frame = video_frame_from_bgr(image, timestamp=123)
self.assertEqual(len(frame.data), 460800)
self.assertEqual(frame.width, 640)
self.assertEqual(frame.height, 480)
self.assertEqual(frame.pts, 123)
async def recv(self):
frame = await self.track.recv()
self.counter += 1
# apply image processing to frame
if self.transform == 'edges':
img = video_frame_to_bgr(frame)
edges = cv2.cvtColor(cv2.Canny(img, 100, 200), cv2.COLOR_GRAY2BGR)
return video_frame_from_bgr(edges, timestamp=frame.pts)
elif self.transform == 'rotate':
img = video_frame_to_bgr(frame)
rows, cols, _ = img.shape
M = cv2.getRotationMatrix2D((cols / 2, rows / 2), self.counter * 1.8, 1)
rotated = cv2.warpAffine(img, M, (cols, rows))
return video_frame_from_bgr(rotated, timestamp=frame.pts)
else:
return frame
async def recv(self):
timestamp = await self.next_timestamp()
# rotate image
rows, cols, _ = self.img.shape
M = cv2.getRotationMatrix2D((cols / 2, rows / 2), self.counter / 2, 1)
rotated = cv2.warpAffine(self.img, M, (cols, rows))
frame = video_frame_from_bgr(rotated, timestamp=timestamp)
self.counter += 1
return frame
async def recv(self):
timestamp = await self.next_timestamp()
return video_frame_from_bgr(self.data_bgr, timestamp=timestamp)