Spaces:
Running
on
CPU Upgrade
Running
on
CPU Upgrade
Update app.py
Browse files
app.py
CHANGED
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@@ -22,24 +22,25 @@ def preprocess_image(img):
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print(f"After conversion to tensor - shape: {img.shape}")
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# Ensure
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if img.ndim == 2:
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img = img.unsqueeze(0)
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elif img.ndim == 3
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print(f"After ensuring
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# Ensure 3 channel image
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if img.shape[
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img = img.
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elif img.shape[
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img = img[:3] # Take only the first 3 channels if more than 3
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print(f"After ensuring 3 channels - shape: {img.shape}")
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# Add batch dimension
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img = img.unsqueeze(0)
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print(f"Final tensor shape: {img.shape}")
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return img
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@@ -70,4 +71,4 @@ with gr.Blocks(theme='huggingface') as demo_app:
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gr.Examples(examples=examples, inputs=[input_image1, input_image2])
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if __name__ == "__main__":
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demo_app.launch()
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print(f"After conversion to tensor - shape: {img.shape}")
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# Ensure 4D tensor (B, C, H, W)
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if img.ndim == 2:
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img = img.unsqueeze(0).unsqueeze(0)
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elif img.ndim == 3:
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if img.shape[0] in [1, 3]:
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img = img.unsqueeze(0)
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else:
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img = img.unsqueeze(1)
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elif img.ndim == 4:
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if img.shape[1] not in [1, 3]:
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img = img.permute(0, 3, 1, 2)
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print(f"After ensuring 4D - shape: {img.shape}")
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# Ensure 3 channel image
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if img.shape[1] == 1:
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img = img.repeat(1, 3, 1, 1)
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elif img.shape[1] > 3:
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img = img[:, :3] # Take only the first 3 channels if more than 3
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print(f"Final tensor shape: {img.shape}")
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return img
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gr.Examples(examples=examples, inputs=[input_image1, input_image2])
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if __name__ == "__main__":
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demo_app.launch(share=True)
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