Update README.md
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@@ -66,12 +66,13 @@ python test.py --clip_path ./sample_videos/clips/v32 \
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Note that we use 216\*384 images for training, which has aspect ratio of 1:2. During inference, we scale the input to this size and then rescale the output back to the original size.
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## Colorization results
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## Comparison with State-of-the-Arts
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<figure>
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<img src='assets/sample1.png'/>
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</figure>
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## More results
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<figure>
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<img src='assets/sample2.png' />
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</figure>
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