Update app.py

app.py

@@ -18,11 +18,6 @@ def predict_image(image):
     Process the uploaded image and return the top 3 predictions.
     """
     try:
-        # Decode the base64 image string back to a PIL.Image object
-        image_data = base64.b64decode(image)
-        image = Image.open(BytesIO(image_data))
-        image = image.convert("RGB")  # Ensure RGB format
-
         # Preprocess the image
         image = image.resize((224, 224))  # ResNet152 expects 224x224 input
         image_array = img_to_array(image)
@@ -41,7 +36,6 @@ def predict_image(image):
         return {"Error": str(e)}
 
 # Create the Gradio interface
-"""
 interface = gr.Interface(
     fn=predict_image,
     inputs=gr.Image(type="pil"),  # Accepts an image input
@@ -50,17 +44,7 @@ interface = gr.Interface(
     description="Upload an image, and the model will predict what's in the image.",
     examples=["dog.jpg", "cat.jpg"],  # Example images for users to test
 )
-"""
-
-interface = gr.Interface(
-    fn=predict_image,
-    inputs=gr.Textbox(label="Base64 Image String"),  # Accepts base64-encoded string
-    outputs=gr.Label(num_top_classes=3),  # Shows top 3 predictions with confidence
-    title="ResNet152 Image Classifier",
-    description="Upload an image as a Base64 string, and the model will predict what's in the image.",
-)
-
 
 # Launch the Gradio app
 if __name__ == "__main__":
-    interface.launch()
+    interface.launch()