| #import gradio as gr | |
| # def greet(name): | |
| # return "Hello " + name + "!!" | |
| # iface = gr.Interface(fn=greet, inputs="text", outputs="text") | |
| # iface.launch() | |
| from fastai.vision.all import * | |
| import gradio as gr | |
| def is_cat(x): return x[0].isupper() | |
| learn = load_learner('model.pkl') | |
| categories = ('Dog', 'Cat') | |
| def classify_image(img): | |
| pred,idx, probs = learn.predict(img) | |
| return dict(zip(categories, map(float,probs))) | |
| #image = gr.inputs.Image(shape=(192,192)) | |
| #label = gr.outputs.label() | |
| #examples = ['cat.jpg'] | |
| #intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) | |
| intf = gr.Interface(fn=classify_image, | |
| inputs=gr.Image(type="pil"), | |
| outputs=gr.Label(num_top_classes=3), | |
| examples=["cat.jpg"]) | |
| intf.launch(inline=False) | |