Update app.py

app.py

@@ -45,12 +45,29 @@ def predict_from_image(image_url):
     try:
         # Download the image from the provided URL
         response = requests.get(image_url)
+        response.raise_for_status()  # Check if the request was successful
         image = Image.open(BytesIO(response.content))
-        # Process the image...
-        return {"result": "Image processed successfully"}
+
+        # Apply transformations
+        image_tensor = transform(image).unsqueeze(0)  # Add batch dimension
+
+        # Perform prediction
+        with torch.no_grad():
+            outputs = model(image_tensor)
+            predicted_class = torch.argmax(outputs, dim=1).item()
+
+        # Interpret the result
+        if predicted_class == 0:
+            return {"result": "The photo is of fall army worm with problem ID 126."}
+        elif predicted_class == 1:
+            return {"result": "The photo is of a healthy maize image."}
+        else:
+            return {"error": "Unexpected class prediction."}
+
     except Exception as e:
         return {"error": str(e)}
 
+
 demo = gr.Interface(
     fn=predict_from_image,
     inputs="text",