async def recv(self):
# 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 = frame_from_bgr(rotated)
self.counter += 1
# sleep
if self.last:
delta = self.last + VIDEO_PTIME - time.time()
if delta > 0:
await asyncio.sleep(delta)
self.last = time.time()
return frame
async def recv(self):
frame = await self.received.get()
self.counter += 1
if (self.counter % 100) > 50:
# apply image processing to frame
if self.transform == 'edges':
img = frame_to_bgr(frame)
edges = cv2.Canny(img, 100, 200)
return frame_from_gray(edges)
elif self.transform == 'rotate':
img = frame_to_bgr(frame)
rows, cols, _ = img.shape
M = cv2.getRotationMatrix2D((cols / 2, rows / 2), self.counter * 7.2, 1)
rotated = cv2.warpAffine(img, M, (cols, rows))
return frame_from_bgr(rotated)
elif self.transform == 'green':
return VideoFrame(width=frame.width, height=frame.height)
else:
return frame
else:
# return raw frame
return frame
async def recv(self):
coros = [track.recv() for track in self.tracks]
frames = await asyncio.gather(*coros)
data_bgrs = [frame_to_bgr(frame) for frame in frames]
data_bgr = numpy.hstack(data_bgrs)
return frame_from_bgr(data_bgr)
def __init__(self, width, height, color):
data_bgr = numpy.zeros((height, width, 3), numpy.uint8)
data_bgr[:, :] = color
self.frame = frame_from_bgr(data_bgr)
def test_frame_from_bgr(self):
image = numpy.full((480, 640, 3), (0, 0, 0), numpy.uint8)
frame = frame_from_bgr(image)
self.assertEqual(len(frame.data), 460800)
self.assertEqual(frame.width, 640)
self.assertEqual(frame.height, 480)
async def recv(self):
ret, frame = self.cap.read()
return frame_from_bgr(frame)