import os import gradio as gr from datasets import load_dataset auth_token = os.environ.get("auth_token") visit_bench_all = load_dataset("mlfoundations/VisIT-Bench", use_auth_token=auth_token) print('visit_bench_all') print(visit_bench_all) print('dataset keys:') print(visit_bench_all.keys()) dataset_keys = list(visit_bench_all.keys()) assert len(dataset_keys) == 1 dataset_key = dataset_keys[0] visit_bench = visit_bench_all[dataset_key] print('first item:') print(visit_bench[0]) df = visit_bench.to_pandas() print(f"Got {len(df)} items in dataframe") df = df.sample(frac=1) df['image'] = df['image'].apply(lambda x: f'') cols = list(df.columns) cols.insert(0, cols.pop(cols.index('image'))) df = df.reindex(columns=cols) LINES_NUMBER = 20 df.drop(columns=['visual'],inplace=True) def display_df(): df_images = df.head(LINES_NUMBER) return df_images def display_next(dataframe, end): start = int(end or len(dataframe)) end = int(start) + int(LINES_NUMBER) global df if end >= len(df) - 1: start = 0 end = LINES_NUMBER df = df.sample(frac=1) print(f"Shuffle") df_images = df.iloc[start:end] assert len(df_images) == LINES_NUMBER return df_images, end initial_dataframe = display_df() # Gradio Blocks with gr.Blocks() as demo: style = """ """ gr.HTML(style) # This line embeds your CSS in the interface gr.Markdown("

VisIT-Bench Dataset Viewer

") with gr.Row(): num_end = gr.Number(visible=False) b1 = gr.Button("Get Initial dataframe") b2 = gr.Button("Next Rows") with gr.Row(): out_dataframe = gr.Dataframe( value=initial_dataframe, row_count=LINES_NUMBER, interactive=False, datatype=["markdown", "str", "str", "bool", "bool", "bool", "str", "str", "str"], # min_width=100, column_widths=[300, 120, 120, 120, 120, 120, 120, 120, 120, 120] ) b1.click(fn=display_df, outputs=out_dataframe, api_name="initial_dataframe") b2.click(fn=display_next, inputs=[out_dataframe, num_end], outputs=[out_dataframe, num_end], api_name="next_rows") demo.launch(debug=True, show_error=True)