VicFonch
commited on
app.py: try-catch cuda bug when try to execte the model
Browse files
app.py
CHANGED
@@ -21,7 +21,7 @@ transform = Compose([
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Normalize(mean=[0.5]*3, std=[0.5]*3),
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])
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def to_numpy(img_tensor):
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img_np = denorm(img_tensor, mean=[0.5]*3, std=[0.5]*3).squeeze().permute(1, 2, 0).cpu().numpy()
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img_np = np.clip(img_np, 0, 1)
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return (img_np * 255).astype(np.uint8)
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@@ -30,21 +30,25 @@ def interpolate(img0_pil, img2_pil, tau=0.5, num_samples=1):
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img0 = transform(img0_pil.convert("RGB")).unsqueeze(0).to(device)
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img2 = transform(img2_pil.convert("RGB")).unsqueeze(0).to(device)
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demo = gr.Interface(
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fn=interpolate,
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Normalize(mean=[0.5]*3, std=[0.5]*3),
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])
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def to_numpy(img_tensor: torch.Tensor) -> np.ndarray:
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img_np = denorm(img_tensor, mean=[0.5]*3, std=[0.5]*3).squeeze().permute(1, 2, 0).cpu().numpy()
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img_np = np.clip(img_np, 0, 1)
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return (img_np * 255).astype(np.uint8)
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img0 = transform(img0_pil.convert("RGB")).unsqueeze(0).to(device)
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img2 = transform(img2_pil.convert("RGB")).unsqueeze(0).to(device)
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try:
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if num_samples == 1:
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# Unique image
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img1 = model.reverse_process([img0, img2], tau)
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return Image.fromarray(to_numpy(img1)), None
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else:
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# Múltiples imágenes → video
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frames = [to_numpy(img0)]
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for t in np.linspace(0, 1, num_samples):
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img = model.reverse_process([img0, img2], float(t))
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frames.append(to_numpy(img))
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frames.append(to_numpy(img2))
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temp_path = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False).name
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imageio.mimsave(temp_path, frames, fps=8)
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return None, temp_path
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except Exception as e:
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print(f"Error during interpolation: {e}")
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return None, None
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demo = gr.Interface(
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fn=interpolate,
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