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import gradio as gr |
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import os |
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import uuid |
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import cv2 |
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from mask import FaceSwapper |
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swapper = FaceSwapper( |
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model_path="models/inswapper_128.onnx", |
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gfpgan_model_path="gfpgan/weights/GFPGANv1.4.pth" |
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) |
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def swap_faces(source_img, target_img): |
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try: |
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source_path = f"temp_source_{uuid.uuid4().hex}.jpg" |
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target_path = f"temp_target_{uuid.uuid4().hex}.jpg" |
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output_path = f"img/result_{uuid.uuid4().hex}.jpg" |
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cv2.imwrite(source_path, cv2.cvtColor(source_img, cv2.COLOR_RGB2BGR)) |
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cv2.imwrite(target_path, cv2.cvtColor(target_img, cv2.COLOR_RGB2BGR)) |
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result_img = swapper.merge_face_into_image(source_path, target_path, output_path) |
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if os.path.exists(source_path): |
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os.remove(source_path) |
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if os.path.exists(target_path): |
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os.remove(target_path) |
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return result_img |
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except Exception as e: |
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return f"❌ حصل خطأ: {str(e)}" |
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demo = gr.Interface( |
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fn=swap_faces, |
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inputs=[ |
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gr.Image(type="numpy", label="Source Image (الطفل)"), |
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gr.Image(type="numpy", label="Target Image (المشهد)") |
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], |
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outputs=gr.Image(type="numpy", label="النتيجة"), |
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title="FaceSwap with GFPGAN", |
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description="ارفع صورتين: (1) صورة الطفل (2) المشهد اللي عايز تدخله فيه. وهنرجعلك صورة face swap محسّنة بـ GFPGAN." |
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) |
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if __name__ == "__main__": |
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demo.launch() |
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