| import fastai.vision.all import * | |
| import gradio as gr | |
| learn = load_learner('model.pkl') | |
| categories = ('wet','tawny','horned') | |
| def classify_image(img): | |
| pred,idx,probs = learn.predict(img) | |
| return dict(zip(categories, map(float,probs))) | |
| image = gr.inputs.Image(shape=(224,224)) | |
| label = gr.outputs.label() | |
| examples = ['harpy.jpg','horned.jpg'] | |
| iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) | |
| iface.launch() | |