Update app.py

app.py

@@ -1,4 +1,3 @@
-
 import os
 import gradio as gr
 from transformers import pipeline, DetrForObjectDetection, DetrConfig, DetrImageProcessor
@@ -35,25 +34,6 @@ model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50", config
 image_processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
 od_pipe = pipeline(task='object-detection', model=model, image_processor=image_processor)
 
-def get_pipeline_prediction(pil_image):
-    # Run the object detection pipeline
-    pipeline_output = od_pipe(pil_image)
-    
-    # Draw the detection results on the image
-    processed_image = draw_detections(pil_image, pipeline_output)
-    
-    # Provide both the image and the JSON detection results
-    return processed_image, pipeline_output
-
-demo = gr.Interface(
-    fn=get_pipeline_prediction,
-    inputs=gr.Image(label="Input image", type="pil"),
-    outputs=[
-        gr.Image(label="Annotated Image"),
-        gr.JSON(label="Detected Objects")
-    ]
-)
-
 def get_pipeline_prediction(pil_image):
     try:
         # Run the object detection pipeline
@@ -69,5 +49,14 @@ def get_pipeline_prediction(pil_image):
         print(f"An error occurred: {str(e)}")
         # Return a message and an empty JSON
         return pil_image, {"error": str(e)}
-        
+
+demo = gr.Interface(
+    fn=get_pipeline_prediction,
+    inputs=gr.Image(label="Input image", type="pil"),
+    outputs=[
+        gr.Image(label="Annotated Image"),
+        gr.JSON(label="Detected Objects")
+    ]
+)
+
 demo.launch()