face_swap.py

import gradio as gr
import requests
import tempfile
import os

# Hugging Face API Config
HF_API_TOKEN = "YOUR_HF_API_KEY"  # Apna token lagao
MODEL_URL = "https://api-inference.huggingface.co/models/deepinsight/inswapper"
HEADERS = {"Authorization": f"Bearer {HF_API_TOKEN}"}

def swap_face(video_file, face_image):
    """🎥 Video + Face → AI Swapped Video"""
    if video_file is None or face_image is None:
        return None

    try:
        # Save temp video
        temp_vid = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")
        with open(temp_vid.name, "wb") as f:
            f.write(video_file.read())

        # Save temp face image
        temp_face = tempfile.NamedTemporaryFile(delete=False, suffix=".png")
        face_image.save(temp_face.name)

        # Send to Hugging Face model (if supports both inputs together)
        files = {
            "video": open(temp_vid.name, "rb"),
            "target_face": open(temp_face.name, "rb")
        }

        resp = requests.post(MODEL_URL, headers=HEADERS, files=files)

        if resp.status_code != 200:
            print("Error:", resp.text)
            return None

        # Save output
        temp_output = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")
        with open(temp_output.name, "wb") as f:
            f.write(resp.content)

        return temp_output.name
    except Exception as e:
        print(f"Error: {e}")
        return None

# ---------- Gradio UI ----------
with gr.Blocks() as demo:
    gr.Markdown("<h2 style='text-align:center'>🤖 AI Face Swap Video — SaEdit MultiAi</h2>")

    vid_input = gr.File(type="file", file_types=[".mp4"], label="🎥 Upload Target Video")
    face_input = gr.Image(type="pil", label="🖼 Upload Face Image")
    btn = gr.Button("🔄 Swap Face")
    output_video = gr.Video(label="🎬 Face Swapped Output")

    btn.click(swap_face, inputs=[vid_input, face_input], outputs=output_video)

if __name__ == "__main__":
    demo.launch()