Create app.py

app.py

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+import torch
+import torchvision import transforms, models
+from PIL import Image
+import fradio as gr
+
+#model initialization
+model= models.resnet18(pretrained=True)
+
+model.fc = torch.nn.Linear(model.fc.in_features,2)
+state_dict=torch.load('up500Model.pt', map_location='cpu')
+model.load_state_dict(state_dict)
+model.eval
+
+#predictions
+imgTransforms = transforms.Comporse([transforms.Resize(256), transforms.CenterCrop(224), trasforms.ToTensor(),transforms.Normalize([0.485,0.456,0.406],[0.229,0.224,0.225])])
+
+LABELS =['Fiat 500', 'VW Up']
+def predict(inp):
+    inp= Image.fromarray(inp.astype('unit8'), 'RGB')
+    inp =imgTransfroms(inp).unsqueeze(0)
+
+    with torch.no_grad():
+        predictions = torch.nn.functional.softmax(model(inp)[0])
+
+    return {LABELS[i]: float(predictions[i]) for i in range(2)}
+examples=[["fiat500.jpg"],["VWUP.jpg"]]
+interface = gr.Interface(predict, input='image', outputs'label', title='App', description= 'upload your car image', examples=examples, cache_examples= False)
+interface.launch()