Create app.py

app.py

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+import gradio as gr
+from utils.preprocessing import ImageProcessor
+
+# Initialize processor (model path relative to repo)
+processor = ImageProcessor("models/best.pt")
+
+def process_image(input_image):
+    if input_image is None:
+        raise gr.Error("Please upload an image first!")
+    
+    # Convert Gradio Image to bytes
+    _, img_bytes = cv2.imencode(".png", input_image)
+    
+    # Process image
+    results = processor.process_image(img_bytes.tobytes())
+    
+    # Format outputs
+    return {
+        class_name: (mask * 255).astype(np.uint8)
+        for class_name, mask in results.items()
+    }
+
+# Gradio interface with enhanced UX
+with gr.Blocks(title="Fashion Segmenter") as demo:
+    gr.Markdown("# 🧥 Fashion Item Segmenter")
+    
+    with gr.Row():
+        input_image = gr.Image(label="Upload Clothing Image", type="numpy")
+        output_gallery = gr.Gallery(label="Segmented Items", columns=2)
+    
+    with gr.Row():
+        run_btn = gr.Button("Process Image", variant="primary")
+        examples = gr.Examples(
+            examples=["sample1.jpg", "sample2.jpg"],
+            inputs=[input_image],
+            label="Example Images"
+        )
+
+    run_btn.click(
+        fn=process_image,
+        inputs=[input_image],
+        outputs=[output_gallery],
+        show_progress=True
+    )
+
+if __name__ == "__main__":
+    demo.launch()