Update app.py

app.py

@@ -73,44 +73,40 @@ def postprocess_image(tensor):
     image = np.transpose(image, (1, 2, 0))
     return (image * 255).astype(np.uint8)
 
-def deblur_image(input_image):
-    if input_image is None:
+def deblur_image(file):
+    if file is None:
         return None
     
     try:
-        # Convert to PIL Image
-        if isinstance(input_image, np.ndarray):
-            input_image = Image.fromarray(input_image)
-        
+        # Load the image from the uploaded file
+        input_image = Image.open(file.name).convert("RGB")
+
         # Save original size
         original_size = input_image.size
-        
+
         # Preprocess
         input_tensor = transform(input_image).unsqueeze(0).to(device)
-        
+
         # Inference
         with torch.no_grad():
             output_tensor = model(input_tensor)
-        
+
         # Postprocess
         output_image = postprocess_image(output_tensor[0])
-        
+
         # Resize back to original size
         output_image = Image.fromarray(output_image).resize(original_size)
         return np.array(output_image)
-    
+
     except Exception as e:
         print(f"Error processing image: {e}")
         return None
 
-# ✅ Custom CSS to hide preview and disable dragging
+# ✅ Custom CSS for styling
 custom_css = """
-/* Hide image preview */
-input[type="file"] {
-    opacity: 0 !important;
-    height: 0px !important;
-    width: 0px !important;
-    position: absolute !important;
+/* Hide Gradio's footer and header */
+footer, header, .gradio-footer, .gradio-header {
+    display: none !important;
 }
 
 /* Non-draggable images */
@@ -120,7 +116,7 @@ img {
     user-select: none !important;
 }
 
-/* Style adjustments */
+/* Styling adjustments */
 body, .gradio-container {
     background-color: #000000 !important;
     color: white !important;
@@ -141,15 +137,12 @@ body, .gradio-container {
     color: white !important;
     border: 1px solid #333333 !important;
 }
-footer, header, .gradio-footer, .gradio-header {
-    display: none !important;
-}
 """
 
-# ✅ Gradio interface
+# ✅ Gradio interface using gr.File (no preview) with custom CSS
 demo = gr.Interface(
     fn=deblur_image,
-    inputs=gr.Image(type="numpy", label="Upload Blurry Image"),
+    inputs=gr.File(label="Upload Blurry Image (No Preview)", type="file"),
     outputs=gr.Image(type="numpy", label="Deblurred Result"),
     title="Image Deblurring",
     description="Upload a blurry image and get it deblurred using deep learning.",