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Is it possible to get good results without pretraining? #12

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sherif7810 opened this issue Feb 19, 2019 · 9 comments
Open

Is it possible to get good results without pretraining? #12

sherif7810 opened this issue Feb 19, 2019 · 9 comments

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@sherif7810
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I over-fit on a small sample of TotalText, until I got a loss of about 0.1 in 6 images, but the demo file with the trained checkpoint doesn't show any contours.
0_img11
1_img12

@sherif7810
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Reducing thresholds adds red dots to output with the runtime of demo increased a lot.

@princewang1994
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It seems that model is underfitting but not overfitting. The loss should be smaller than 0.1. For small dataset overfit, you can try smaller learning rate and training more epochs.

@sherif7810
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Do you know a configuration (Number of samples, batch size, epochs, learning rate, etc) that is guaranteed to overfit successfully?
I can't increase batch size to 4.

@sherif7810
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Re-downloading the repository fixed the issue. It seems I broke something.

@sherif7810
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You can close the issue. Thanks for help.

@dongzhi0312
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为什么输出的识别结果图片好像被重复了一次
0_img91

@princewang1994
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princewang1994 commented Mar 20, 2019

@dongzhi0312 这个地方代码中有点小问题,在demo.py里面这个部分,这了predict和gt使用了相同的coutour变量,其实下面那张图片应该是使用meta变量中的坐标点的,你发的这张图片的上下两个应该都是predict,我会在接下来的版本中改正~

@dongzhi0312
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dongzhi0312 commented Mar 21, 2019

把这段代码改写成下面这样,解决了图像重复一次的问题
demo.py 中的85 86 行注释,88行改为 cv2.imwrite(path, predict_vis) 解决了图像重复的问题。图像重复问题由 86的 np.concatenate() 造成的。

@sherif7810
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sherif7810 commented Mar 24, 2019

What is the best training configuration for generalization on test set? This is with batch size of 2:
Screenshot from 2019-03-24 15-57-07
Blue: Training. Red: Testing.

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3 participants