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| import requests | |
| import zipfile | |
| import gradio as gr | |
| from src.examples import audio_examples_tab, examples_tab | |
| from src.mk_attacks_variations import mk_audio_variations, mk_image_variations | |
| from src.mk_leaderboard import mk_leaderboard | |
| from pathlib import Path | |
| abs_path = Path(__file__).parent | |
| with gr.Blocks(theme=gr.themes.Base()) as demo: | |
| gr.Markdown( | |
| """ | |
| # 🥇 Omni Seal Bench Watermarking Leaderboard | |
| """ | |
| ) | |
| with gr.Tabs(): | |
| with gr.Tab("Audio"): | |
| gr.Markdown( | |
| """ | |
| ### Performance on Ravdess dataset | |
| """ | |
| ) | |
| mk_leaderboard( | |
| abs_path / "data/audio_benchmark.csv", | |
| default_selection=[ | |
| "TimeDomain_bit_acc", | |
| "AmplitudeDomain_bit_acc", | |
| "identity_snr", | |
| "identity_bit_acc", | |
| "identity_detect_prob", | |
| "avg_bit_acc", | |
| "avg_tn_bit_acc", | |
| "avg_detect_prob", | |
| "avg_tn_detect_prob", | |
| ], | |
| core_columns=["model", "snr"], | |
| filter_columns=["model"], | |
| search_columns=["model"], | |
| categories={ | |
| "speed": "Time", | |
| "updownresample": "Time", | |
| "echo": "Time", | |
| "random_noise": "Amplitude", | |
| "lowpass_filter": "Amplitude", | |
| "highpass_filter": "Amplitude", | |
| "bandpass_filter": "Amplitude", | |
| "smooth": "Amplitude", | |
| "boost_audio": "Amplitude", | |
| "duck_audio": "Amplitude", | |
| "shush": "Amplitude", | |
| }, | |
| ) | |
| mk_audio_variations(abs_path / "data/audio_attacks_variations.csv") | |
| with gr.Tab("Image"): | |
| gr.Markdown( | |
| """ | |
| ### Performance on Val2014 dataset | |
| """ | |
| ) | |
| mk_leaderboard( | |
| abs_path / "data/image_benchmark.csv", | |
| default_selection=[ | |
| "Visual_bit_acc", | |
| "Geometric_bit_acc", | |
| "Compression_bit_acc", | |
| "Inpainting_bit_acc", | |
| "Mixed_bit_acc", | |
| "avg_bit_acc", | |
| "avg_p_value", | |
| "avg_word_acc", | |
| ], | |
| core_columns=[ | |
| "model", | |
| "psnr", | |
| "ssim", | |
| "lpips", | |
| ], | |
| filter_columns=[ | |
| "model", | |
| ], | |
| search_columns=["model"], | |
| categories={ | |
| "proportion": "Geometric", | |
| "collage": "Inpainting", | |
| "crop": "Geometric", | |
| "rot": "Geometric", | |
| "jpeg": "Compression", | |
| "brightness": "Visual", | |
| "contrast": "Visual", | |
| "saturation": "Visual", | |
| "sharpness": "Visual", | |
| "resize": "Geometric", | |
| "overlay_text": "Inpainting", | |
| "hflip": "Geometric", | |
| "perspective": "Geometric", | |
| "median_filter": "Visual", | |
| "hue": "Visual", | |
| "gaussian_blur": "Visual", | |
| "comb": "Mixed", | |
| "avg": "Averages", | |
| "none": "Baseline", | |
| }, | |
| ) | |
| mk_image_variations(abs_path / "data/image_attacks_variations.csv") | |
| with gr.Tab("Image examples"): | |
| examples_tab(abs_path) | |
| with gr.Tab("Audio examples"): | |
| audio_examples_tab(abs_path) | |
| with gr.Tab("Docs"): | |
| README_URL = "https://raw.githubusercontent.com/facebookresearch/omnisealbench/refs/heads/main/README.md" | |
| def fetch_readme(): | |
| response = requests.get(README_URL, timeout=4) | |
| if response.status_code == 200: | |
| return response.text | |
| else: | |
| return "Failed to fetch README.md. Please check the URL or try again later." | |
| # Define the Gradio interface | |
| gr.Markdown(fetch_readme()) | |
| if __name__ == "__main__": | |
| demo.launch(ssr_mode=False) | |