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python - cv2 Farneback 光流量值太低

转载 作者:行者123 更新时间:2023-12-02 16:04:19 29 4
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我正在尝试计算两帧之间的光流,然后使用计算出的光流扭曲前一帧。我发现 cv2 有 Farneback Optical FLow,所以我用它来计算 Flow。我从 cv2 tutorial 中获取了默认参数我正在使用 this answer 中给出的代码扭曲框架.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)。

进一步调试,发现计算出来的流量值偏低。为什么会这样?我做错了什么吗?

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

输入图像: Image1 Image2

输出:
扭曲的图像与上一张图像完全相同,但它应该看起来像下一张图像。
enter image description here

感谢任何帮助!

最佳答案

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]。将其改回 [0,255] 成功了!

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

关于python - cv2 Farneback 光流量值太低,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/61647936/

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