Upload app.py

app.py

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+import gradio as gr
+import insightface
+from insightface.app import FaceAnalysis
+from PIL import Image
+import numpy as np
+
+# ---------- HTML description ----------
+wellcomingMessage = """
+    <h1>Face Swap</h1>
+    <p>by <a href="https://www.tonyassi.com/" target="_blank" style="color:#97d8be;">Tony Assi</a></p>
+    <h2>Try out <a href="https://huggingface.co/spaces/tonyassi/video-face-swap" target="_blank">Video Face Swap</a> ❤️</h2>
+"""
+
+# ---------- Check version ----------
+assert insightface.__version__ >= '0.7'
+
+# ---------- Initialize models ----------
+app = FaceAnalysis(name='buffalo_l')
+app.prepare(ctx_id=0, det_size=(640, 640))
+
+# ensure model downloads fully; safer with download=True and zip=True like your working version
+swapper = insightface.model_zoo.get_model('inswapper_128.onnx', download=True, download_zip=True)
+
+# ---------- Swap logic ----------
+def swap_faces(src_img, dest_img):
+    src_faces = app.get(src_img)
+    dest_faces = app.get(dest_img)
+
+    if len(src_faces) == 0 or len(dest_faces) == 0:
+        raise gr.Error("No faces detected in one of the images.")
+
+    # Just swap first detected face from each image
+    source_face = src_faces[0]
+    dest_face = dest_faces[0]
+    result = swapper.get(dest_img, dest_face, source_face, paste_back=True)
+
+    return Image.fromarray(np.uint8(result)).convert("RGB")
+
+# ---------- Interface ----------
+gr.Interface(
+    fn=swap_faces,
+    inputs=[gr.Image(), gr.Image()],
+    outputs=gr.Image(),
+    description=wellcomingMessage,
+    examples=[
+        ['./Images/kim.jpg', './Images/marilyn.jpg'],
+    ],
+).launch()