Update app.py

app.py

@@ -18,13 +18,16 @@ def run_inference(image):
     detections = results.pandas().xyxy[0]
 
     # Count objects by category
-    object_counts = detections['name'].value_counts().to_dict()
+    object_counts = detections['name'].value_counts()
+
+    # Create a formatted string to show object counts
+    count_text = "\n".join([f"{obj}: {count}" for obj, count in object_counts.items()])
 
     # Convert the annotated image from BGR to RGB for display
     annotated_image = results.render()[0]
     annotated_image = cv2.cvtColor(annotated_image, cv2.COLOR_BGR2RGB)
 
-    return annotated_image, object_counts
+    return annotated_image, count_text
 
 # Create the Gradio interface
 interface = gr.Interface(
@@ -32,7 +35,7 @@ interface = gr.Interface(
     inputs=gr.Image(type="pil"),
     outputs=[
         gr.Image(type="pil"),
-        gr.JSON(label="Object Counts")  # Add JSON output for object counts
+        gr.Textbox(label="Object Counts", lines=5, interactive=False)  # Display counts as text
     ],
     title="YOLOv5 Object Detection with Counts",
     description="Upload an image to run YOLOv5 object detection, see the annotated results, and view the count of detected objects by category."