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Browse files- README.md +25 -13
- app.py +32 -0
- requirements.txt +6 -0
README.md
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# Faceless Video Generator (Free)
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This is a minimal talking avatar video generator app using open-source models.
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## Setup
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1. Install dependencies:
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```bash
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pip install -r requirements.txt
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```
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2. Run the app:
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```bash
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python app.py
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```
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3. Open the URL displayed in your terminal in your browser.
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4. Upload your avatar image and enter text to generate talking avatar videos.
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## Notes
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- This uses the First Order Motion Model (https://github.com/AliaksandrSiarohin/first-order-model) for animation.
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- Coqui TTS is used for text-to-speech.
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- Model weights will be downloaded automatically on first run.
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app.py
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from huggingface_hub import snapshot_download
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import gradio as gr
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import subprocess
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import os
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import uuid
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def setup_models():
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if not os.path.exists("checkpoints"):
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print("Downloading model...")
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snapshot_download(repo_id="deepinsight/first-order-model", local_dir="checkpoints")
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setup_models()
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def generate(text, image):
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session = str(uuid.uuid4())[:8]
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os.makedirs(f"results/{session}", exist_ok=True)
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image_path = f"results/{session}/avatar.jpg"
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image.save(image_path)
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audio_path = f"results/{session}/audio.wav"
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tts_cmd = f'tts --text "{text}" --out_path {audio_path}'
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subprocess.run(tts_cmd, shell=True, check=True)
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video_cmd = f'python checkpoints/inference.py --driven_audio {audio_path} --source_image {image_path} --result_dir results/{session}'
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subprocess.run(video_cmd, shell=True, check=True)
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return f"results/{session}/video.mp4"
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gr.Interface(
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fn=generate,
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inputs=[gr.Textbox(label="Script"), gr.Image(label="Avatar Image", type="pil")],
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outputs=gr.Video(label="Generated Video"),
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title="Faceless Video Generator (Free)",
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description="Type your message + upload an image. Get a talking avatar video!"
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).launch()
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requirements.txt
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gradio
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huggingface_hub
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tts
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torch
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opencv-python
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numpy
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