我正在尝试计算两个帧之间的光通量,然后使用计算出的光流扭曲前一帧。我发现cv2具有Farneback Optical FLow,因此我正在使用它来计算Flow。我从cv2 tutorial中获取了默认参数,然后使用this answer中提供的代码对框架进行了变形。但是,当我看到扭曲的帧时,它与前一帧完全一样,并且没有变化(数组相等)。
通过进一步的调试,我发现计算出的流量值太低。为什么会这样呢?我做错什么了吗?
代码:
def get_optical_flow(prev_frame: numpy.ndarray, next_frame: numpy.ndarray) -> numpy.ndarray:
prev_gray = skimage.color.rgb2gray(prev_frame)
next_gray = skimage.color.rgb2gray(next_frame)
flow = cv2.calcOpticalFlowFarneback(prev_gray, next_gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
return flow
def warp_frame(prev_frame: numpy.ndarray, flow: numpy.ndarray):
h, w = flow.shape[:2]
flow = -flow
flow[:,:,0] += numpy.arange(w)
flow[:,:,1] += numpy.arange(h)[:,numpy.newaxis]
# res = cv2.remap(img, flow, None, cv2.INTER_LINEAR)
next_frame = cv2.remap(prev_frame, flow, None, cv2.INTER_LINEAR)
return next_frame
def demo1():
prev_frame_path = Path('./frame025.png')
next_frame_path = Path('./frame027.png')
prev_frame = skimage.io.imread(prev_frame_path.as_posix())
next_frame = skimage.io.imread(next_frame_path.as_posix())
flow = get_optical_flow(prev_frame, next_frame)
print(f'Flow: max:{flow.max()}, min:{flow.min()}, mean:{flow.__abs__().mean()}')
warped_frame = warp_frame(prev_frame, flow)
print(numpy.array_equal(prev_frame, warped_frame))
pyplot.subplot(1,3,1)
pyplot.imshow(prev_frame)
pyplot.subplot(1,3,2)
pyplot.imshow(next_frame)
pyplot.subplot(1,3,3)
pyplot.imshow(warped_frame)
pyplot.show()
return
输出:扭曲图像与上一幅图像完全相同,而后一幅图像应看起来像下一幅图像。
感谢您的任何帮助!
问题在于将rgb帧转换为灰色。 skimage.color.rgb2gray()
将强度范围从[0,255]
更改为[0,1]
。将其更改回[0,255]
可行!
def get_optical_flow(prev_frame: numpy.ndarray, next_frame: numpy.ndarray) -> numpy.ndarray:
prev_gray = (skimage.color.rgb2gray(prev_frame) * 255).astype('uint8')
next_gray = (skimage.color.rgb2gray(next_frame) * 255).astype('uint8')
flow = cv2.calcOpticalFlowFarneback(prev_gray, next_gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
return flow