| from huggingface_hub import snapshot_download | |
| import gradio as gr | |
| import subprocess | |
| import os | |
| import uuid | |
| def setup_models(): | |
| if not os.path.exists("checkpoints"): | |
| print("Downloading model...") | |
| snapshot_download(repo_id="deepinsight/first-order-model", local_dir="checkpoints") | |
| setup_models() | |
| def generate(text, image): | |
| session = str(uuid.uuid4())[:8] | |
| os.makedirs(f"results/{session}", exist_ok=True) | |
| image_path = f"results/{session}/avatar.jpg" | |
| image.save(image_path) | |
| audio_path = f"results/{session}/audio.wav" | |
| tts_cmd = f'tts --text "{text}" --out_path {audio_path}' | |
| subprocess.run(tts_cmd, shell=True, check=True) | |
| video_cmd = f'python checkpoints/inference.py --driven_audio {audio_path} --source_image {image_path} --result_dir results/{session}' | |
| subprocess.run(video_cmd, shell=True, check=True) | |
| return f"results/{session}/video.mp4" | |
| gr.Interface( | |
| fn=generate, | |
| inputs=[gr.Textbox(label="Script"), gr.Image(label="Avatar Image", type="pil")], | |
| outputs=gr.Video(label="Generated Video"), | |
| title="Faceless Video Generator (Free)", | |
| description="Type your message + upload an image. Get a talking avatar video!" | |
| ).launch() |