Update app.py

app.py

@@ -3,52 +3,54 @@ import requests
 from PIL import Image
 from io import BytesIO
 
-# Roboflow model configuration
+# Roboflow config
 API_URL = "https://detect.roboflow.com"
 API_KEY = "dxkgGGHSZ3DI8XzVn29U"
 WORKSPACE = "naveen-kumar-hnmil"
 WORKFLOW = "detect-count-and-visualize-5"
 
-# Detection function with logging
 def detect_image_with_log(image):
     try:
-        # Convert uploaded image to bytes
+        # Convert to JPEG bytes
         buffered = BytesIO()
         image.save(buffered, format="JPEG")
         image_bytes = buffered.getvalue()
 
-        # Roboflow endpoint
+        # Build API endpoint
         endpoint = f"{API_URL}/{WORKSPACE}/{WORKFLOW}?api_key={API_KEY}"
 
-        # Make POST request to Roboflow
+        # POST to Roboflow
         response = requests.post(
             endpoint,
             files={"file": image_bytes},
             data={"confidence": "0.4", "overlap": "0.3"}
         )
 
-        # Check response
+        # If API call failed
         if response.status_code != 200:
-            return None, f"❌ Error: {response.status_code} - {response.text}"
+            return None, f"❌ API error: {response.status_code}\n{response.text}"
 
-        json_data = response.json()
-        image_url = json_data.get("image", {}).get("url")
+        # Parse response
+        result_json = response.json()
+        annotated_url = result_json.get("image", {}).get("url")
 
-        if not image_url:
-            return None, f"❌ Error: No image URL in response.\nResponse: {json_data}"
+        if not annotated_url:
+            return None, f"❌ No 'image.url' found in response.\nResponse: {result_json}"
 
-        # Fetch annotated image
-        annotated_response = requests.get(image_url)
-        if annotated_response.status_code != 200:
-            return None, f"❌ Failed to download result image.\nURL: {image_url}"
+        # Download annotated image
+        image_response = requests.get(annotated_url)
+        if image_response.status_code != 200:
+            return None, f"❌ Failed to load annotated image.\nURL: {annotated_url}"
 
-        annotated_img = Image.open(BytesIO(annotated_response.content))
-        return annotated_img, "✅ Detection successful."
+        # Show result
+        result_image = Image.open(BytesIO(image_response.content))
+        return result_image, "✅ Detection successful."
 
     except Exception as e:
-        return None, f"❌ Exception occurred: {str(e)}"
+        # Catch and return all exceptions
+        return None, f"❌ Exception: {str(e)}"
 
-# Gradio UI
+# Gradio app
 interface = gr.Interface(
     fn=detect_image_with_log,
     inputs=gr.Image(type="pil", label="Upload a Solar Panel Image"),
@@ -57,9 +59,8 @@ interface = gr.Interface(
         gr.Textbox(label="Detection Log")
     ],
     title="Solar Panel Fault Detection",
-    description="Upload an image to detect cracks, dents, and faulty parts using a Roboflow-trained YOLOv8 model.",
-    allow_flagging="never",
-    theme="default"
+    description="Upload an image to detect cracks, dents, and faults using a Roboflow-trained YOLOv8 model.",
+    allow_flagging="never"
 )
 
 if __name__ == "__main__":