| import torch | |
| model = torch.hub.load('model.pkl') | |
| import requests | |
| from PIL import Image | |
| from torchvision import transforms | |
| # Download human-readable labels for ImageNet. | |
| learn=load_learner('model.pkl') | |
| categories=('Dogs','Cats') | |
| def classify_img(img): | |
| pred,idx,probs=learn.predict(img) | |
| return dict(zip(categories,map(float,probs))) | |
| import gradio as gr | |
| image =gr.inputs.Image(shape=(192,192)) | |
| label =gr.outputs.Label() | |
| examples=['dog.jpg'] | |
| intf=gr.Interface(fn=classify_img,inputs=image,outputs=label,examples=examples) | |
| intf.launch(inline=False) | |