Update app.py

app.py

@@ -30,6 +30,8 @@ coco_metadata = MetadataCatalog.get("coco_2017_val_panoptic")
 # import Mask2Former project
 from mask2former import add_maskformer2_config
 
+from PIL import Image
+
 cfg = get_cfg()
 cfg.MODEL.DEVICE='cpu'
 add_deeplab_config(cfg)
@@ -41,6 +43,8 @@ cfg.MODEL.MASK_FORMER.TEST.INSTANCE_ON = True
 cfg.MODEL.MASK_FORMER.TEST.PANOPTIC_ON = True
 predictor = DefaultPredictor(cfg)
 
+os.system("wget https://i.imgur.com/Vj17K5z.jpg")
+
 def inference(img):
     im = cv2.imread(img)
     outputs = predictor(im)
@@ -57,7 +61,7 @@ title = "Detectron 2"
 description = "Gradio demo for Detectron 2: A PyTorch-based modular object detection library. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."
 article = "<p style='text-align: center'><a href='https://ai.facebook.com/blog/-detectron2-a-pytorch-based-modular-object-detection-library-/' target='_blank'>Detectron2: A PyTorch-based modular object detection library</a> | <a href='https://github.com/facebookresearch/detectron2' target='_blank'>Github Repo</a></p>"
 
-examples = [['airplane.png']]
+examples = [['Vj17K5z.jpg']]
 
 gr.Interface(inference, inputs=gr.inputs.Image(type="filepath"), outputs=[gr.outputs.Image(label="Panoptic segmentation",type="pil"),gr.outputs.Image(label="instance segmentation",type="pil"),gr.outputs.Image(label="semantic segmentation",type="pil")],enable_queue=True, title=title,
     description=description,