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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()
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