| from fastai.vision.all import * | |
| import gradio as gr | |
| def is_cat(x): return [0].isupper() | |
| learn = load_learner('model.pkl') | |
| categories = ('Dog', 'Cat') | |
| #define funciton for gradio to call | |
| def classify_image(img): | |
| pred,idx,probs = learn.predice(img) | |
| return dict(zip(categories, map(float,probs))) #gradio wants a dict of labels and probabilities of each | |
| image = gr.inputs.Image(shape=(192, 192)) | |
| label = gr.outputs.Label() | |
| examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg'] | |
| intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=example) | |
| intf.launch(inline=False) |