Update app.py

app.py

@@ -13,7 +13,6 @@ class Predictor:
         self.setup()
 
     def setup(self):
-        # Models are already in /app/models thanks to Dockerfile
         model_dir = "models"
 
         print("Loading models...")
@@ -31,13 +30,14 @@ class Predictor:
         self.face_analyser.prepare(ctx_id=0, det_size=(640, 640))
 
     def get_face(self, img_data):
+        """Return the largest detected face"""
         faces = self.face_analyser.get(img_data)
         if len(faces) == 0:
             return None
-        # Return the largest face
         return max(faces, key=lambda x: (x.bbox[2] - x.bbox[0]) * (x.bbox[3] - x.bbox[1]))
 
     def predict(self, target_image, swap_image):
+        """Face swap function"""
         try:
             frame = cv2.imread(target_image)
             source = cv2.imread(swap_image)
@@ -51,10 +51,10 @@ class Predictor:
             if target_face is None or source_face is None:
                 return None, "❌ Could not detect a clear face in one or both images."
 
-            # Face swap
+            # Perform face swap
             result = self.face_swapper.get(frame, target_face, source_face, paste_back=True)
 
-            # Enhancement
+            # Enhance with GFPGAN
             _, _, result = self.face_enhancer.enhance(result, paste_back=True)
 
             # Save result
@@ -68,45 +68,48 @@ class Predictor:
             return None, f"❌ Error: {str(e)}"
 
 
-# Load predictor once at startup
+# Load the predictor once at startup
 predictor = Predictor()
 
-# Modern UI with examples
+# Clean UI without examples
 with gr.Blocks(title="Swap Face Model", theme=gr.themes.Soft()) as demo:
     gr.Markdown("# 😻 Face Swap Model")
-    gr.Markdown("Upload a target image and a face to swap in. Works best with clear, well-lit frontal faces.")
+    gr.Markdown("Upload a **target image** and a **face to swap in**. Works best with clear, well-lit frontal faces.")
 
     with gr.Row():
         with gr.Column():
-            target_input = gr.Image(type="filepath", label="Target Image", height=450)
+            target_input = gr.Image(
+                type="filepath", 
+                label="Target Image (the photo you want to change)", 
+                height=450
+            )
         with gr.Column():
-            swap_input = gr.Image(type="filepath", label="Swap Face Image", height=450)
+            swap_input = gr.Image(
+                type="filepath", 
+                label="Swap Face Image (the face you want to use)", 
+                height=450
+            )
 
     with gr.Row():
         swap_btn = gr.Button("🔄 Swap Faces", variant="primary", size="large")
 
     with gr.Row():
-        output_image = gr.Image(type="filepath", label="Result", height=500)
+        output_image = gr.Image(
+            type="filepath", 
+            label="Result", 
+            height=500
+        )
 
     status = gr.Textbox(label="Status", interactive=False)
 
-    # Examples (add your own sample images to the repo)
-    gr.Examples(
-        examples=[["examples/target1.jpg", "examples/swap1.jpg"],
-                  ["examples/target2.jpg", "examples/swap2.jpg"]],
-        inputs=[target_input, swap_input],
-        outputs=[output_image, status],
-        fn=predictor.predict,
-        cache_examples=False
-    )
-
+    # Button action
     swap_btn.click(
         fn=predictor.predict,
         inputs=[target_input, swap_input],
         outputs=[output_image, status]
     )
 
-    gr.Markdown("**Tips:** Use high-resolution photos. Results are better with similar lighting and angles.")
+    gr.Markdown("**Tips:**\n• Use high-resolution, well-lit photos\n• Frontal or near-frontal faces work best\n• Results improve with similar lighting and angles.")
 
 if __name__ == "__main__":
     demo.launch(