app.py

import gradio as gr
import numpy as np
import cv2
import onnxruntime
from insightface.app import FaceAnalysis
from pathlib import Path

# Initialize Face Analysis
face_analyzer = FaceAnalysis(name="buffalo_l")
face_analyzer.prepare(ctx_id=0, det_size=(640, 640))

# Load Face Swapper Model
MODEL_PATH = Path("models/inswapper_128.onnx")
if not MODEL_PATH.exists():
    raise FileNotFoundError("Model file inswapper_128.onnx not found.")

session = onnxruntime.InferenceSession(str(MODEL_PATH))

def swap_faces(source_img, target_img):
    """Perform face swapping using the ONNX model."""
    try:
        # Convert images to correct format
        source_img = cv2.cvtColor(np.array(source_img), cv2.COLOR_RGB2BGR)
        target_img = cv2.cvtColor(np.array(target_img), cv2.COLOR_RGB2BGR)

        # Detect faces
        source_faces = face_analyzer.get(source_img)
        target_faces = face_analyzer.get(target_img)

        if not source_faces or not target_faces:
            return "No faces detected in one or both images."
        if len(source_faces) > 1 or len(target_faces) > 1:
            return "Multiple faces detected; only one face per image is supported."

        source_face = source_faces[0]
        target_face = target_faces[0]

        # Prepare input data for ONNX model
        input_data = {
            "target_image": target_img,
            "target_face": target_face.embedding,
            "source_face": source_face.embedding
        }

        # Run the ONNX model
        result = session.run(None, input_data)[0]

        # Convert result to image format
        result_img = np.clip(result * 255, 0, 255).astype(np.uint8)
        result_img = cv2.cvtColor(result_img, cv2.COLOR_BGR2RGB)

        return result_img
    except Exception as e:
        return f"Face swap failed: {e}"

# Gradio UI
with gr.Blocks() as demo:
    gr.Markdown("# Face Swap Tool 🚀")
    with gr.Row():
        input_source = gr.Image(label="Source Face", type="pil")
        input_target = gr.Image(label="Target Image", type="pil")
    btn_swap = gr.Button("Swap Faces")
    output_image = gr.Image(label="Swapped Face")
    btn_swap.click(swap_faces, inputs=[input_source, input_target], outputs=output_image)

# Launch Gradio App
demo.launch()