我正在尝试使用python和通过skimage进行模板匹配来进行视频稳定。该代码应该在整个视频中跟踪单个点，但是跟踪非常不精确，我怀疑它甚至无法正常工作

这是 track_point 函数，应该将视频作为输入和点的一些坐标，然后返回跟踪点的数组每帧

from skimage.feature import match_template
from skimage.color import rgb2gray

def track_point(video,x,y,patch_size = 4,search_size = 40):

    length,height,width,_ = video.shape

    frame = rgb2gray(np.squeeze(video[1,:,:])) # convert image to grayscale
    x1 = int(max(1,x - patch_size / 2))
    y1 = int(max(1,y - patch_size / 2))
    x2 = int(min(width,x + patch_size / 2 - 1))
    y2 = int(min(height,y + patch_size / 2 - 1))
    template = frame[y1:y2,x1:x2] # cut the reference patch (template) from the first frame
    track_x = [x]
    track_y = [y]
    #plt.imshow(template)
    half = int(search_size/2)
    for i in range(1,length):
        prev_x = int(track_x[i-1])
        prev_y = int(track_y[i-1])
        frame = rgb2gray(np.squeeze(video[i,:])) # Extract current frame and convert it grayscale
        image = frame[prev_x-half:prev_x+half,prev_y-half:prev_y+half] # Cut-out a region of search_size x search_size from 'frame' with the center in the point's previous position (i-1)
        result = match_template(image,template,pad_input=False,mode='constant',constant_values=0) # Compare the region to template using match_template
        ij = np.unravel_index(np.argmax(result),result.shape) # Select best match (maximum) and determine its position. Update x and y and append new x,y values to track_x,track_y

        x,y = ij[::-1] 
        x += x1
        y += y1
        track_x.append(x)
        track_y.append(y)

    return track_x,track_y

这是该功能的实现

points = track_point(video,point[0],point[1])
# Draw trajectory on top of the first frame from video
image = np.squeeze(video[1,:]) 
figure = plt.figure()
plt.gca().imshow(image) 
plt.gca().plot(points[0],points[1]) 

我希望剧情能够以某种方式正常播放，因为视频并不那么摇摇欲坠，但事实并非如此。

由于某种原因，图形绘制了搜索模板的几乎所有坐标。

编辑：这是视频的链接：https://upload-video.net/a11073n9Y11-noau

我在做什么错了？