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Don't depend on torchvision.
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commit
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@ -1,9 +1,9 @@
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import torch
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import torchvision
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import math
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import struct
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import comfy.checkpoint_pickle
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import safetensors.torch
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import numpy as np
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from PIL import Image
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def load_torch_file(ckpt, safe_load=False, device=None):
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@ -349,9 +349,9 @@ def bislerp(samples, width, height):
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return result
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def lanczos(samples, width, height):
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images = [torchvision.transforms.functional.to_pil_image(image) for image in samples]
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images = [Image.fromarray(np.clip(255. * image.movedim(0, -1).cpu().numpy(), 0, 255).astype(np.uint8)) for image in samples]
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images = [image.resize((width, height), resample=Image.Resampling.LANCZOS) for image in images]
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images = [torchvision.transforms.functional.to_tensor(image) for image in images]
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images = [torch.from_numpy(np.array(image).astype(np.float32) / 255.0).movedim(-1, 0) for image in images]
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result = torch.stack(images)
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return result
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