How to make this work for custom videos

[abhinavsagar]

[pch9520]

Recently I have a try. Firstly,I calibrate my camera parameter with the calibrate_camera.py; secondly,I calibrate meters to pixel of my picture taken by my camera; Thirdly,I amend the parameters in line_fit.py perspective_transform.py and line_fit_video.py Now,I can use this code to detect lines in my video but in some moment the detection is not accurate

[StephanieCoding]

### When I use my own videos to test, this error often occurs. Anyone knows which parameters should I amend?

C:\Users\moon5\Anaconda3\python.exe D:/Documents/Desktop/智能驾驶/advanced_lane_detection-master/advanced_lane_detection-master/line_fit_video.py Traceback (most recent call last): File "D:/Documents/Desktop/智能驾驶/advanced_lane_detection-master/advanced_lane_detection-master/line_fit_video.py", line 104, in annotate_video('video_1.mp4', 'out.mp4') File "D:/Documents/Desktop/智能驾驶/advanced_lane_detection-master/advanced_lane_detection-master/line_fit_video.py", line 98, in annotate_video annotated_video = video.fl_image(annotate_image) File "C:\Users\moon5\Anaconda3\lib\site-packages\moviepy\video\VideoClip.py", line 514, in fl_image return self.fl(lambda gf, t: image_func(gf(t)), apply_to) File "C:\Users\moon5\Anaconda3\lib\site-packages\moviepy\Clip.py", line 137, in fl newclip = self.set_make_frame(lambda t: fun(self.get_frame, t)) File "", line 2, in set_make_frame File "C:\Users\moon5\Anaconda3\lib\site-packages\moviepy\decorators.py", line 14, in outplace f(newclip, *a, **k) File "C:\Users\moon5\Anaconda3\lib\site-packages\moviepy\video\VideoClip.py", line 669, in set_make_frame self.size = self.get_frame(0).shape[:2][::-1] File "", line 2, in get_frame File "C:\Users\moon5\Anaconda3\lib\site-packages\moviepy\decorators.py", line 89, in wrapper return f(*new_a, **new_kw) File "C:\Users\moon5\Anaconda3\lib\site-packages\moviepy\Clip.py", line 94, in get_frame return self.make_frame(t) File "C:\Users\moon5\Anaconda3\lib\site-packages\moviepy\Clip.py", line 137, in newclip = self.set_make_frame(lambda t: fun(self.get_frame, t)) File "C:\Users\moon5\Anaconda3\lib\site-packages\moviepy\video\VideoClip.py", line 514, in return self.fl(lambda gf, t: image_func(gf(t)), apply_to) File "D:/Documents/Desktop/智能驾驶/advanced_lane_detection-master/advanced_lane_detection-master/line_fit_video.py", line 43, in annotate_image ret = line_fit(binary_warped) File "D:\Documents\Desktop\智能驾驶\advanced_lane_detection-master\advanced_lane_detection-master\line_fit.py", line 79, in line_fit left_fit = np.polyfit(lefty, leftx, 2) File "C:\Users\moon5\Anaconda3\lib\site-packages\numpy\lib\polynomial.py", line 550, in polyfit raise TypeError("expected non-empty vector for x") TypeError: expected non-empty vector for x

[pch9520]

Did you feed your video straightly without amending any parameter? If so ,it's normal to encounter issues. @StephanieCoding

[neishka]

I am facing the same issue, @pch9520 what parameters are you referring to.

[pch9520]

I am facing the same issue, @pch9520 what parameters are you referring to.

If you want to feed your own video,I think the following parameters you should amend: 1.the size of each frame picture; 2.some parameters in perspective_transform.py to fit your scene src = np.float32( [[200, 720], [1100, 720], [595, 450], [685, 450]]) dst = np.float32( [[300, 720], [980, 720], [300, 0], [980, 0]]) @neishka

[Phillweston]

I am facing the same issue, @pch9520 what parameters are you referring to.

If you want to feed your own video,I think the following parameters you should amend: 1.the size of each frame picture; 2.some parameters in perspective_transform.py to fit your scene src = np.float32( [[200, 720], [1100, 720], [595, 450], [685, 450]]) dst = np.float32( [[300, 720], [980, 720], [300, 0], [980, 0]]) @neishka

What do you mean by the parameters? If I use my own video, how can I adjust the above parameters to get the best recognition effect?

[pch9520]

Hello, @Phillweston 你可以看看这篇解析（网上还有很多其他的）： https://zhuanlan.zhihu.com/p/46146266 如果你要在自己的视频上用，就要先调整联合阈值的参数，把车道线部分过滤出来，然后再调整鸟瞰图参数，设置你的感兴趣区域并将前视图映射到俯视图，就可以了 如果你还要得出具体的车辆曲率和车辆偏离车道中心的距离，还需要修改距离标定参数（横纵向一个像素分别映射到现实世界是多少距离（m），在俯视图上进行标定）