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import os
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from os import path
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import glob
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import numpy as np
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from PIL import Image
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from diffusers.utils import export_to_gif
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import torch
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ROOT = '/projects/katefgroup/datasets/gs_kubric/InpaintingFormat_Set50'
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OUT_ROOT = os.path.join(ROOT, 'Consistent4D')
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RESOLUTION = 512
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imset = '2017/consistent4d.txt'
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os.makedirs(OUT_ROOT, exist_ok=True)
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device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
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mask_dir = path.join(ROOT, 'MergedAnnotations')
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image_dir = path.join(ROOT, 'JPEGImages')
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videos = []
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num_frames = {}
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vid_names = os.listdir(image_dir)
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for _video in vid_names:
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videos.append(_video)
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num_frames[_video] = len(os.listdir(path.join(image_dir, _video)))
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for index in range(len(videos)):
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video = videos[index]
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if video == 'swing-human-only':
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continue
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all_frames = []
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img_paths = glob.glob(path.join(image_dir, video + '/*'))
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img_paths.sort()
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mask_paths = glob.glob(path.join(mask_dir, video, '001' + '/*'))
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mask_paths.sort()
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os.makedirs(os.path.join(OUT_ROOT, video), exist_ok=True)
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for f in range(10):
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img = Image.open(img_paths[f]).convert('RGBA')
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img = img.resize((RESOLUTION, RESOLUTION))
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mask = Image.open(mask_paths[f])
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mask = mask.resize((RESOLUTION, RESOLUTION))
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binary_mask = np.array(mask) > 128
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binary_mask = np.tile(binary_mask[:, :, np.newaxis], (1,1,4))
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masked_img = Image.fromarray(np.array(img) * binary_mask).convert('RGBA')
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masked_img.save(os.path.join(OUT_ROOT, video, f'{f}.png')) |
