Update app.py

app.py

@@ -7,7 +7,13 @@ import gradio as gr
 #os.system("wget https://raw.githubusercontent.com/pytorch/hub/master/imagenet_classes.txt")
 
 #model = torch.hub.load('huawei-noah/ghostnet', 'ghostnet_1x', pretrained=True)
-model = torch.jit.load('https://huggingface.co/spaces/yuhe6/final_project/blob/main/Net_Rotate9.pth').eval().to(device)
+#model = torch.jit.load('https://huggingface.co/spaces/yuhe6/final_project/blob/main/Net_Rotate9.pth').eval().to(device)
+
+
+model = torch.jit.load('Net_Blur_jit.pt', map_location = torch.device('cpu'))
+model.eval()
+
+
 #torch.hub.download_url_to_file('https://huggingface.co/spaces/yuhe6/final_project/blob/main/Net_Rotate9.pth', '/tmp/temporary_file')
 #model = torch.hub.load('/tmp', 'temporary_file', pretrained=True)
 
@@ -48,7 +54,7 @@ def inference(input_image):
     return result
 
 inputs = gr.inputs.Image(type='pil')
-outputs = gr.outputs.Label(type="confidences",num_top_classes=5)
+outputs = gr.outputs.Label(type="confidences",num_top_classes=1)
 
 title = "GHOSTNET"
 description = "Gradio demo for GHOSTNET, Efficient networks by generating more features from cheap operations. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."