taesiri commited on
Commit
b49939e
1 Parent(s): c69d7bc
Files changed (2) hide show
  1. README.md +1 -1
  2. app.py +31 -15
README.md CHANGED
@@ -4,7 +4,7 @@ emoji: 💻
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  colorFrom: blue
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  colorTo: red
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  sdk: gradio
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- sdk_version: 3.0.5
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  app_file: app.py
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  pinned: true
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  ---
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  colorFrom: blue
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  colorTo: red
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  sdk: gradio
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+ sdk_version: 4.13
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  app_file: app.py
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  pinned: true
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  ---
app.py CHANGED
@@ -28,6 +28,15 @@ gdown.cached_download(
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  md5="b1228503d5a89eef7e35e2cbf86b2fc0",
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  )
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  # EXTRACT
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  torchvision.datasets.utils.extract_archive(
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  from_path="GTA-V-Embeddings.zip",
@@ -35,13 +44,21 @@ torchvision.datasets.utils.extract_archive(
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  remove_finished=False,
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  )
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- # Load videos from Dataset
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- gta_v_videos = load_dataset("taesiri/GamePhysics_Grand_Theft_Auto_V")
 
 
 
 
 
 
 
 
 
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  post_id_to_video_path = {
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- os.path.splitext(os.path.basename(x))[0]: x
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- for x in gta_v_videos["Grand_Theft_Auto_V"][:]["video_file_path"]
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  }
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- # Initialize CLIP model
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  clip.available_models()
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@@ -179,22 +196,22 @@ def main():
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  value="A person flying in the air",
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  label="Query",
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  ),
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- gr.Radio(list_of_games, label="Game To Search"),
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- gr.Radio(["ViT-B/32"], label="MODEL"),
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- gr.Radio(["Majority", "Top-K"], label="Aggregator"),
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  gr.Slider(300, 2000, label="Pool Size", value=1000),
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  ],
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  outputs=[
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- gr.Textbox(type="auto", label="Search Params"),
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- gr.Video(type="mp4", label="Result 1"),
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  gr.Markdown(),
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- gr.Video(type="mp4", label="Result 2"),
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  gr.Markdown(),
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- gr.Video(type="mp4", label="Result 3"),
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  gr.Markdown(),
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- gr.Video(type="mp4", label="Result 4"),
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  gr.Markdown(),
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- gr.Video(type="mp4", label="Result 5"),
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  gr.Markdown(),
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  ],
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  examples=[
@@ -244,7 +261,6 @@ def main():
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  blocks.launch(
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  debug=True,
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- enable_queue=True,
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  )
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  md5="b1228503d5a89eef7e35e2cbf86b2fc0",
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  )
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+
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+ gdown.cached_download(
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+ url="https://huggingface.co/datasets/taesiri/GamePhysics_Grand_Theft_Auto_V/resolve/main/GTA-V-Videos.zip?download=true",
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+ path="./GTA-V-Videos.zip",
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+ quiet=False,
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+ md5="14d8374a7d1f09c13b5c99fe4d0dc4f1",
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+ )
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+
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+
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  # EXTRACT
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  torchvision.datasets.utils.extract_archive(
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  from_path="GTA-V-Embeddings.zip",
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  remove_finished=False,
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  )
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+
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+ # EXTRACT
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+ torchvision.datasets.utils.extract_archive(
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+ from_path="GTA-V-Videos.zip",
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+ to_path="./",
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+ remove_finished=False,
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+ )
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+
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+
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+ list_of_all_videos = glob("GTA-V-Videos/*.mp4")
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+
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  post_id_to_video_path = {
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+ os.path.splitext(os.path.basename(x))[0]: x for x in list_of_all_videos
 
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  }
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+
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  clip.available_models()
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  value="A person flying in the air",
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  label="Query",
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  ),
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+ gr.Radio(list_of_games, label="Game To Search", value=list_of_games[0]),
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+ gr.Radio(["ViT-B/32"], label="Model", value="ViT-B/32"),
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+ gr.Radio(["Majority", "Top-K"], label="Aggregator", value="Majority"),
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  gr.Slider(300, 2000, label="Pool Size", value=1000),
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  ],
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  outputs=[
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+ gr.Textbox(label="Search Params"),
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+ gr.Video(label="Result 1"),
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  gr.Markdown(),
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+ gr.Video(label="Result 2"),
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  gr.Markdown(),
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+ gr.Video(label="Result 3"),
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  gr.Markdown(),
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+ gr.Video(label="Result 4"),
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  gr.Markdown(),
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+ gr.Video(label="Result 5"),
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  gr.Markdown(),
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  ],
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  examples=[
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  blocks.launch(
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  debug=True,
 
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  )
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