Upload with huggingface_hub

app.py

@@ -4,27 +4,25 @@ from torchvision import transforms
 from PIL import ImageOps
 
 def load_model():
-    model_dict = torch.load('linear_model.pt')
+    model_dict = torch.load('gradio-app/linear_model.pt')
     return model_dict
 
 model = load_model()
 convert_tensor = transforms.ToTensor()
 
 def predict(img):
-    img =  ImageOps.grayscale(img)
+    img =  ImageOps.grayscale(img).resize((28,28))
     image_tensor = convert_tensor(img).view(28*28)
     res = image_tensor @ model['weights'] + model['bias']
     res = res.sigmoid()
     return {"It's 3": float(res), "It's 7": float(1-res)}
 
 title = "Is it 7 or 3"
-description = '<p><center>Upload an image with a handwritten number: 7 or 3.</center></p>'
-examples = ['three.png', 'seven.png']
+description = '<p><center>Write a number, 7 or 3, in the middle.</center></p>'
 
 gr.Interface(fn=predict, 
-             inputs=gr.Image(type="pil"),
+             inputs=gr.Paint(type="pil", invert_colors=True),
              outputs=gr.Label(num_top_classes=2),
              title=title,
              description=description,
-             allow_flagging='never',
-             examples=examples).launch()
+             allow_flagging='never').launch()