import pandas as pd import gradio as gr from ui.leaderboard import render_leader_board, render_info_html from ui.df_arena_tool import render_tool_info from ui.submission import render_submission_page import os from utils import load_leaderboard from huggingface_hub import snapshot_download import gradio as gr import os import json REPO_ID = os.getenv('REPO_ID') DB_ERR_PATH = f'./data/data/leaderboard_err.csv' DB_ACCURACY_PATH = f'./data/data/leaderboard_accuracy.csv' CITATIONS_PATH = f'./data/data/model_citations.json' if not os.path.exists('./data/data'): snapshot_download(repo_id=REPO_ID, repo_type="dataset", local_dir='./data/data') with open(CITATIONS_PATH, 'r') as f: model_citations = json.load(f) # Load leaderboard data leaderboard_df_err = load_leaderboard(DB_ERR_PATH) leaderboard_df_accuracy = load_leaderboard(DB_ACCURACY_PATH) # Function to load leaderboard data custom_css = """ h1, { font-size: 50px !important; /* Increase heading sizes */ line-height: 2.0 !important; /* Increase line spacing */ text-align: center !important; /* Center align headings */ } .gradio-container { padding: 30px !important; /* Increase padding around the UI */ } .markdown-body p { font-size: 30px !important; /* Increase text size */ line-height: 2.0 !important; /* More space between lines */ } .gradio-container .gr-block { margin-bottom: 20px !important; /* Add more space between elements */ } """ # Gradio Interface Configuration def create_ui(): with gr.Blocks(theme=gr.themes.Soft(text_size=gr.themes.sizes.text_lg), css=custom_css) as demo: # gr.Markdown("# Speech Deep Fake Arena") gr.Image('/data/code/DF_arena_leaderboard/leaderboard/data/df_arena.jpg') with gr.Tabs(): with gr.Tab("🏆 Leaderboard"): with gr.Column(): render_info_html() gr.Markdown("Table for Equal Error Rate (EER %) for different systems") render_leader_board(leaderboard_df_err, model_citations) # Adjust this to work with Gradio components gr.Markdown("Table for Accuracy (EER %) for different systems") render_leader_board(leaderboard_df_accuracy, model_citations) with gr.Tab("🛠 Evaluation"): render_tool_info() with gr.Tab("📤 Submission"): render_submission_page() return demo # Launch the app create_ui().launch()