Update app.py

app.py

@@ -160,9 +160,8 @@ iface = gr.Interface(
 iface.launch()"""
 
 from PIL import Image
-import numpy as np
-from ultralytics import YOLO
 import gradio as gr
+from ultralytics import YOLO
 
 # Load the YOLO model
 MODEL_URL = 'https://huggingface.co/ayoubsa/yolo_model/resolve/main/best.pt'
@@ -171,13 +170,16 @@ model = YOLO(MODEL_URL)
 # Define the prediction function
 def predict(image):
     try:
-        print("Received image:", type(image))  # Check the type of the received image
+        print("Received image:", type(image))  # Check the type of the received image (should be PIL)
         results = model(image)  # Perform object detection using YOLO
+        
+        # Print details of the results object
+        print("Results:", results)  # Check the contents of results
+        
         results.render()  # Render bounding boxes on the image
         
         output_image = Image.fromarray(results.imgs[0])  # Convert to PIL image
-        
-        print("Predicted image:", type(output_image))  # Ensure output is PIL Image
+        print("Predicted image type:", type(output_image))  # Ensure output is PIL Image
         return output_image
     except Exception as e:
         print("Error during prediction:", e)
@@ -194,3 +196,4 @@ iface = gr.Interface(
 
 # Launch the Gradio app
 iface.launch()
+