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| import gradio as gr | |
| import pandas as pd | |
| block = gr.Blocks(title="LongVideoBench Leaderboard", theme='gradio/soft') | |
| # Function to sort data and filter columns based on checkboxes | |
| def sort_data(key, show_duration, show_category): | |
| data = pd.read_csv("result.csv") | |
| duration_columns = ['8s-15s', '15s-60s', '180s-600s', '900s-3600s'] | |
| category_columns = ['S2E', 'S2O', 'S2A', 'E2O', 'SSS', 'SOS', 'SAA', 'T3E', 'T3O', 'TOS', 'TAA'] | |
| columns_to_show = ['Model', 'Test Total'] | |
| if show_duration: | |
| columns_to_show += duration_columns | |
| if show_category: | |
| columns_to_show += category_columns | |
| columns_to_show += ['Val Total', 'LMM Type', 'Interleaved?', "#Max Frames"] | |
| if key in data.columns: | |
| df_sorted = data.sort_values(by=key, ascending=False) | |
| else: | |
| df_sorted = data.sort_values(by='Test Total', ascending=False) | |
| return df_sorted[columns_to_show] | |
| with block: | |
| gr.HTML("<link rel='stylesheet' type='text/css' href='style.css'>") | |
| with gr.Row(): | |
| gr.Markdown(""" | |
| <div style='text-align: center;'> | |
| <h1>LongVideoBench Leaderboard</h1> | |
| Website: <a href="https://longvideobench.github.io" target="_blank">longvideobench.github.io</a> | |
| </div> | |
| """) | |
| with gr.Tab("Existing Results"): | |
| with gr.Row(): | |
| show_duration = gr.Checkbox(label="Show Test Set Accuracy by Duration Groups", value=False) | |
| show_category = gr.Checkbox(label="Show Test Set Accuracy by Question Categories", value=False) | |
| key_input = gr.Textbox(label="Rank LMMs by column:", placeholder="Test Total (default)") | |
| data_frame = gr.DataFrame(sort_data('Test Total', show_duration=False, show_category=False)) | |
| def update_data_frame(key, show_duration, show_category): | |
| return sort_data(key, show_duration, show_category) | |
| key_input.change(update_data_frame, inputs=[key_input, show_duration, show_category], outputs=data_frame) | |
| show_duration.change(update_data_frame, inputs=[key_input, show_duration, show_category], outputs=data_frame) | |
| show_category.change(update_data_frame, inputs=[key_input, show_duration, show_category], outputs=data_frame) | |
| gr.Markdown("Models are evaluated using their optimal #max frames, capped at 256 frames.") | |
| with gr.Tab("Submit!"): | |
| gr.Markdown( | |
| '''The answer of validation set of LongVideoBench is public now. Please see our [released dataset](https://huggingface.co/datasets/longvideobench/LongVideoBench) for more information. | |
| For test set, please prepare your output as follows: | |
| ```python | |
| {VIDEO_ID_0: "A", VIDEO_ID_1: "D", ...} # Please make sure your submission only contains the letter of model's choice, or starts with the letter of model's choice. | |
| ``` | |
| and submit to us as a JSON file. | |
| Please prepare an email to `[email protected]` titled [LongVideoBench-Submission-YOURNAME] to submit and obtain your results. | |
| _We will launch an automatic submission server soon._''' | |
| ) | |
| block.launch() |