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| from fastai.vision.all import * | |
| import gradio as gr | |
| learn = load_learner('petClassifierModel.pkl') | |
| categories = learn.dls.vocab | |
| 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 = ['basset_hound2.jpg','Border_Collie_dog.jpg','german_sherpherd.jpg','poodle.jpg'] | |
| iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) | |
| iface.launch() |