Create app.py

app.py

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+from PIL import Image
+import torch
+from torchvision import transforms
+
+# load model
+model = torch.hub.load('hustvl/yolop', 'yolop', pretrained=True)
+
+
+normalize = transforms.Normalize(
+        mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]
+    )
+
+transform=transforms.Compose([
+            transforms.ToTensor(),
+            # normalize
+        ])
+
+
+def inference(img):
+
+    # print(img.size)
+    img = img.resize((640, 640))
+
+    img = torch.unsqueeze(transform(img), dim=0)
+
+    # img = transform(img)
+
+    det_out, da_seg_out,ll_seg_out = model(img)
+    ll_out = ll_seg_out[0][0, :, :].detach().numpy()
+    da_out = da_seg_out[0][0, :, :].detach().numpy()
+    return da_out,ll_out
+    
+gr.Interface(inference,gr.inputs.Image(type="pil"),["image","image"]).launch(debug=True)