Create app.py

app.py

@@ -0,0 +1,69 @@
+import gradio as gr  
+import torch  
+from PIL import Image  
+from transformers import AutoFeatureExtractor, AutoModelForImageUpscaling  
+
+def load_model():  
+    try:  
+        feature_extractor = AutoFeatureExtractor.from_pretrained("keras-io/super-resolution")  
+        model = AutoModelForImageUpscaling.from_pretrained("keras-io/super-resolution")  
+        return feature_extractor, model  
+    except Exception as e:  
+        print(f"Model loading error: {e}")  
+        return None, None  
+
+def super_resolve_image(input_image):  
+    # Validate input  
+    if input_image is None:  
+        return None  
+    
+    # Load model (do this once, not in every function call for efficiency)  
+    feature_extractor, model = load_model()  
+    
+    if model is None:  
+        return "Error: Could not load model"  
+    
+    try:  
+        # Convert to PIL Image if not already  
+        if not isinstance(input_image, Image.Image):  
+            input_image = Image.fromarray(input_image)  
+        
+        # Prepare image  
+        inputs = feature_extractor(images=input_image, return_tensors="pt")  
+        
+        # Super-resolve  
+        with torch.no_grad():  
+            outputs = model(**inputs)  
+            enhanced_image = feature_extractor.post_process_image(outputs.image)[0]  
+        
+        return enhanced_image  
+    
+    except Exception as e:  
+        print(f"Super-resolution error: {e}")  
+        return None  
+
+def create_gradio_interface():  
+    with gr.Blocks() as demo:  
+        gr.Markdown("# 🖼️ Simple Image Super-Resolution")  
+        
+        with gr.Row():  
+            input_image = gr.Image(label="Input Image", type="pil")  
+            output_image = gr.Image(label="Super-Resolved Image")  
+        
+        enhance_btn = gr.Button("Enhance Image Resolution")  
+        
+        enhance_btn.click(  
+            fn=super_resolve_image,   
+            inputs=input_image,   
+            outputs=output_image  
+        )  
+    
+    return demo  
+
+# Launch the interface  
+if __name__ == "__main__":  
+    demo = create_gradio_interface()  
+    demo.launch(  
+        server_name="0.0.0.0",   
+        server_port=7860  
+    )