Update app.py

app.py

@@ -255,10 +255,8 @@ def predict(image):
     # Normalize the image
     mean = [0.485, 0.456, 0.406]
     std = [0.229, 0.224, 0.225]
-    
     mean = np.expand_dims(mean, axis=(1,2))
     std = np.expand_dims(std, axis=(1,2))
-    
     image = (image / 255.0 - mean)/std
     
     # Convert the image to a numpy array and add a batch dimension
@@ -268,7 +266,6 @@ def predict(image):
     
     # Make prediction
     output = model.run(None, {input_name: image})
-
     
     print("type output:", type(output))
     print(output)
@@ -281,13 +278,17 @@ def predict(image):
     print("type annotated image:", type(annotated_img))
     print(annotated_img)
 
+    # Convert to PIL Image
+    annotated_img = Image.fromarray(annotated_img)
+
     return annotated_img
     
 # Gradio interface
 demo = gr.Interface(
     fn=predict,
     inputs=gr.Image(sources=["webcam"], type="numpy"),  # Accepts image input
-    outputs="annotatedimage"  # Customize based on your output format
+    # outputs="annotatedimage"  # Customize based on your output format
+    outputs=gr.Image(type="pil"),  # Accepts image input
 )
 
 if __name__ == "__main__":