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4259255
1
Parent(s):
af9aa0c
Update app.py
Browse files
app.py
CHANGED
@@ -24,18 +24,37 @@ def video_identity(video):
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def nan():
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return None
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# demo = gr.Interface(video_identity,
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# gr.Video(),
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# "playable_video",
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# examples=[
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# os.path.join(os.path.dirname(__file__),
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# "videos/rl-video-episode-0.mp4")],
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# cache_examples=True)
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FORMAT = ['mp4', 'gif'][1]
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def
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envs = parse_envs()
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env_name = envs[random.randint(0, len(envs)-1)]
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# choose video
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@@ -53,25 +72,15 @@ def update(user_choice, data_folder='videos'):
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current_time = strftime("%Y-%m-%d-%H-%M-%S", gmtime())
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info = [env_name, user_choice, left, right, current_time]
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print(info)
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writer_object = writer(file)
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writer_object.writerow(info)
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file.close()
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# if FORMAT == 'mp4':
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# left = os.path.join(os.path.dirname(__file__),
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# "videos/rl-video-episode-2.mp4")
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# right = os.path.join(os.path.dirname(__file__),
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# "videos/rl-video-episode-3.mp4")
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# else:
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# left = os.path.join(os.path.dirname(__file__),
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# "videos/rl-video-episode-2.gif")
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# right = os.path.join(os.path.dirname(__file__),
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# "videos/rl-video-episode-3.gif")
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# print(left, right)
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# return left, right
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def replay(left, right):
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return left, right
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def nan():
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return None
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FORMAT = ['mp4', 'gif'][1]
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def get_huggingface_dataset():
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try:
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import huggingface_hub
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except (ImportError, ModuleNotFoundError):
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raise ImportError(
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"Package `huggingface_hub` not found is needed "
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"for HuggingFaceDatasetSaver. Try 'pip install huggingface_hub'."
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)
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HF_TOKEN = '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' # my HF token
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DATASET_NAME = 'crowdsourced-robotinder-demo'
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FLAGGING_DIR = 'flag/'
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path_to_dataset_repo = huggingface_hub.create_repo(
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repo_id=DATASET_NAME,
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token=HF_TOKEN,
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private=False,
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repo_type="dataset",
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exist_ok=True,
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)
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dataset_dir = os.path.join(DATASET_NAME, FLAGGING_DIR)
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repo = huggingface_hub.Repository(
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local_dir=dataset_dir,
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clone_from=path_to_dataset_repo,
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use_auth_token=HF_TOKEN,
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)
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repo.git_pull(lfs=True)
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log_file = os.path.join(dataset_dir, "flag_data.csv")
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return repo, log_file
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def update(user_choice, data_folder=VIDEO_PATH):
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envs = parse_envs()
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env_name = envs[random.randint(0, len(envs)-1)]
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# choose video
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current_time = strftime("%Y-%m-%d-%H-%M-%S", gmtime())
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info = [env_name, user_choice, left, right, current_time]
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print(info)
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repo, log_file = get_huggingface_dataset() # flag without using gradio flagging
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with open(log_file, 'a') as file: # incremental change of the file
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writer_object = writer(file)
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writer_object.writerow(info)
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file.close()
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repo.push_to_hub(commit_message=f"Flagged sample at {current_time}")
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return left, right
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def replay(left, right):
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return left, right
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