Fix multi-frame dataset OBO error
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@ -34,7 +34,7 @@ class BaseUnsupervisedImageDataset(data.Dataset):
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for c in chunks:
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c.reload(opt)
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else:
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chunks = [ChunkWithReference(opt, d) for d in os.scandir(path) if d.is_dir()]
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chunks = [ChunkWithReference(opt, d) for d in sorted(os.scandir(path), key=lambda e: e.name) if d.is_dir()]
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# Prune out chunks that have no images
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res = []
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for c in chunks:
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@ -23,6 +23,7 @@ class MultiFrameDataset(BaseUnsupervisedImageDataset):
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frames_needed -= 1
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search_idx -= 1
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else:
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search_idx += 1
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break
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# Now build num_frames starting from search_idx.
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@ -62,7 +63,7 @@ class MultiFrameDataset(BaseUnsupervisedImageDataset):
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if __name__ == '__main__':
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opt = {
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'name': 'amalgam',
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'paths': ['F:\\4k6k\\datasets\\ns_images\\vixen\\full_video_256_tiled_with_ref'],
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'paths': ['/content/fullvideo_256_tiled_test'],
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'weights': [1],
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'target_size': 128,
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'force_multiple': 32,
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@ -77,13 +78,14 @@ if __name__ == '__main__':
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ds = MultiFrameDataset(opt)
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import os
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os.makedirs("debug", exist_ok=True)
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for i in range(100000, len(ds)):
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for i in [3]:
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import random
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o = ds[random.randint(0, 1000000)]
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o = ds[i]
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k = 'GT'
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v = o[k]
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if 'path' not in k and 'center' not in k:
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fr, f, h, w = v.shape
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for j in range(fr):
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import torchvision
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torchvision.utils.save_image(v[j].unsqueeze(0), "debug/%i_%s_%i.png" % (i, k, j))
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base=osp.basename(o["GT_path"])
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torchvision.utils.save_image(v[j].unsqueeze(0), "debug/%i_%s_%i__%s.png" % (i, k, j, base))
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