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import os |
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import json |
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import logging |
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import numpy as np |
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import clip |
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from PIL import Image |
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import torch |
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import torch.nn as nn |
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import torch.nn.functional as F |
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from vbench.utils import load_video, load_dimension_info, clip_transform |
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from tqdm import tqdm |
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def background_consistency(clip_model, preprocess, video_list, device, read_frame): |
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sim = 0.0 |
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cnt = 0 |
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video_results = [] |
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image_transform = clip_transform(224) |
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for video_path in tqdm(video_list): |
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video_sim = 0.0 |
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if read_frame: |
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video_path = video_path[:-4].replace('videos', 'frames').replace(' ', '_') |
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tmp_paths = [os.path.join(video_path, f) for f in sorted(os.listdir(video_path))] |
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images = [] |
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for tmp_path in tmp_paths: |
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images.append(preprocess(Image.open(tmp_path))) |
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images = torch.stack(images) |
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else: |
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images = load_video(video_path) |
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images = image_transform(images) |
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images = images.to(device) |
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image_features = clip_model.encode_image(images) |
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image_features = F.normalize(image_features, dim=-1, p=2) |
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for i in range(len(image_features)): |
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image_feature = image_features[i].unsqueeze(0) |
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if i == 0: |
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first_image_feature = image_feature |
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else: |
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sim_pre = max(0.0, F.cosine_similarity(former_image_feature, image_feature).item()) |
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sim_fir = max(0.0, F.cosine_similarity(first_image_feature, image_feature).item()) |
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cur_sim = (sim_pre + sim_fir) / 2 |
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video_sim += cur_sim |
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cnt += 1 |
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former_image_feature = image_feature |
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sim_per_image = video_sim / (len(image_features) - 1) |
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sim += video_sim |
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video_results.append({'video_path': video_path, 'video_results': sim_per_image}) |
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sim_per_video = sim / (len(video_list) - 1) |
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sim_per_frame = sim / cnt |
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return sim_per_frame, video_results |
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def compute_background_consistency(json_dir, device, submodules_list): |
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vit_path, read_frame = submodules_list[0], submodules_list[1] |
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clip_model, preprocess = clip.load(vit_path, device=device) |
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video_list, _ = load_dimension_info(json_dir, dimension='background_consistency', lang='en') |
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all_results, video_results = background_consistency(clip_model, preprocess, video_list, device, read_frame) |
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return all_results, video_results |
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