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quantumiracle-git
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19a05d0
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Parent(s):
1955e12
Update app.py
Browse files
app.py
CHANGED
@@ -10,6 +10,12 @@ from csv import writer
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from datasets import load_dataset
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from hfserver import HuggingFaceDatasetSaver, HuggingFaceDatasetJSONSaver
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# download data from huggingface dataset
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# dataset = load_dataset("quantumiracle-git/robotinder-data")
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@@ -89,7 +95,7 @@ def get_huggingface_dataset():
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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, left, right, data_folder=VIDEO_PATH, flag_to_huggingface=True):
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global last_left_video_path
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global last_right_video_path
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global last_infer_left_video_path
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@@ -111,9 +117,11 @@ def update(user_choice, left, right, data_folder=VIDEO_PATH, flag_to_huggingface
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except:
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repo.git_pull(lfs=True) # sync with remote first
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repo.push_to_hub(commit_message=f"Flagged sample at {current_time}")
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# choose video
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videos = os.listdir(os.path.join(data_folder, env_name))
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video_files = []
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@@ -156,22 +164,26 @@ def build_interface(iter=3, data_folder=VIDEO_PATH):
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# build gradio interface
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with gr.Blocks() as demo:
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gr.Markdown("Here is RoboTinder
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gr.Markdown("Select the best robot behaviour in your choice!")
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with gr.Row():
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# some initial values
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envs = parse_envs()
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env_name = envs[random.randint(0, len(envs)-1)] # random pick an env
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# choose video
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videos = os.listdir(os.path.join(data_folder, env_name))
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video_files = []
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for f in videos:
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if f.endswith(f'.{FORMAT}'):
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video_files.append(os.path.join(data_folder, env_name, f))
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# randomly choose two videos
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selected_video_ids = np.random.choice(len(video_files), 2, replace=False)
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left_video_path = video_files[selected_video_ids[0]]
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right_video_path = video_files[selected_video_ids[1]]
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if FORMAT == 'mp4':
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# left = gr.PlayableVideo(left_video_path, label="left_video")
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# right = gr.PlayableVideo(right_video_path, label="right_video")
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@@ -197,13 +209,14 @@ def build_interface(iter=3, data_folder=VIDEO_PATH):
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# btn1 = gr.Button("Replay")
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user_choice = gr.Radio(["Left", "Right", "Not Sure"], label="Which one is your favorite?")
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btn2 = gr.Button("Next")
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# This needs to be called at some point prior to the first call to callback.flag()
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callback.setup([user_choice, left, right], "flagged_data_points")
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# btn1.click(fn=replay, inputs=[left, right], outputs=[left, right])
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btn2.click(fn=update, inputs=[user_choice, left, right], outputs=[left, right])
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# We can choose which components to flag -- in this case, we'll flag all of them
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btn2.click(lambda *args: callback.flag(args), [user_choice, left, right], None, preprocess=False)
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from datasets import load_dataset
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from hfserver import HuggingFaceDatasetSaver, HuggingFaceDatasetJSONSaver
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ENVS = ['ShadowHand', 'ShadowHandCatchAbreast', 'ShadowHandOver', 'ShadowHandBlockStack', 'ShadowHandCatchUnderarm',
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'ShadowHandCatchOver2Underarm', 'ShadowHandBottleCap', 'ShadowHandLiftUnderarm', 'ShadowHandTwoCatchUnderarm',
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'ShadowHandDoorOpenInward', 'ShadowHandDoorOpenOutward', 'ShadowHandDoorCloseInward', 'ShadowHandDoorCloseOutward',
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'ShadowHandPushBlock', 'ShadowHandKettle',
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'ShadowHandScissors', 'ShadowHandPen', 'ShadowHandSwingCup', 'ShadowHandGraspAndPlace', 'ShadowHandSwitch']
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# download data from huggingface dataset
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# dataset = load_dataset("quantumiracle-git/robotinder-data")
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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, left, right, choose_env, data_folder=VIDEO_PATH, flag_to_huggingface=True):
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global last_left_video_path
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global last_right_video_path
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global last_infer_left_video_path
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except:
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repo.git_pull(lfs=True) # sync with remote first
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repo.push_to_hub(commit_message=f"Flagged sample at {current_time}")
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if choose_env == 'Random':
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envs = parse_envs()
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env_name = envs[random.randint(0, len(envs)-1)]
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else:
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env_name = choose_env
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# choose video
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videos = os.listdir(os.path.join(data_folder, env_name))
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video_files = []
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# build gradio interface
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with gr.Blocks() as demo:
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gr.Markdown("Here is **RoboTinder**!")
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gr.Markdown("Select the best robot behaviour in your choice!")
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# some initial values
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envs = parse_envs()
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env_name = envs[random.randint(0, len(envs)-1)] # random pick an env
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with gr.Row():
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str_env_name = gr.Markdown(f"{env_name}")
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# choose video
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videos = os.listdir(os.path.join(data_folder, env_name))
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video_files = []
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for f in videos:
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if f.endswith(f'.{FORMAT}'):
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video_files.append(os.path.join(data_folder, env_name, f))
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# randomly choose two videos
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selected_video_ids = np.random.choice(len(video_files), 2, replace=False)
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left_video_path = video_files[selected_video_ids[0]]
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right_video_path = video_files[selected_video_ids[1]]
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with gr.Row():
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if FORMAT == 'mp4':
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# left = gr.PlayableVideo(left_video_path, label="left_video")
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# right = gr.PlayableVideo(right_video_path, label="right_video")
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# btn1 = gr.Button("Replay")
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user_choice = gr.Radio(["Left", "Right", "Not Sure"], label="Which one is your favorite?")
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choose_env = gr.Radio(["Random"]+ENVS, label="Choose the next task:")
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btn2 = gr.Button("Next")
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# This needs to be called at some point prior to the first call to callback.flag()
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callback.setup([user_choice, left, right], "flagged_data_points")
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# btn1.click(fn=replay, inputs=[left, right], outputs=[left, right])
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btn2.click(fn=update, inputs=[user_choice, left, right, choose_env], outputs=[left, right, str_env_name])
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# We can choose which components to flag -- in this case, we'll flag all of them
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btn2.click(lambda *args: callback.flag(args), [user_choice, left, right], None, preprocess=False)
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