Update app.py

app.py

@@ -43,6 +43,7 @@ gradio_app = gr.Interface(
 if __name__ == "__main__":
     gradio_app.launch()"""
 
+
 import gradio as gr
 from ultralytics import YOLO
 from PIL import Image
@@ -61,12 +62,23 @@ def predict(input_img):
         # Perform inference
         results = model(image_array)
 
+        # Debug: Log the results
+        print(f"Detection results: {results}")
+
         # Extract detected class names
         detected_classes = [model.names[int(cls)] for cls in results[0].boxes.cls]
+        print(f"Detected classes: {detected_classes}")
 
         # Render results on the image
-        rendered_image = results[0].plot()  # This method returns the image with bounding boxes
-        output_image = Image.fromarray(rendered_image)  # Convert the rendered image to a PIL Image
+        rendered_image = results[0].plot()  # Render bounding boxes
+        if rendered_image is None:
+            print("Rendered image is None. Something went wrong in the plot() method.")
+        
+        # Debug: Log image shape after rendering
+        print(f"Rendered image shape: {rendered_image.shape}")
+
+        # Convert the rendered image to a PIL image for output
+        output_image = Image.fromarray(rendered_image)
 
         return output_image, {cls: 1.0 for cls in detected_classes}  # Dummy scores for simplicity
     except Exception as e:
@@ -75,7 +87,7 @@ def predict(input_img):
 
 # Gradio app configuration
 gradio_app = gr.Interface(
-    predict,
+    fn=predict,
     inputs=gr.Image(label="Upload an Image", type="pil"),
     outputs=[
         gr.Image(label="Predicted Image with Bounding Boxes"),  # Rendered image with bounding boxes
@@ -88,3 +100,4 @@ gradio_app = gr.Interface(
 if __name__ == "__main__":
     gradio_app.launch()
 
+