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| # AUTOGENERATED! DO NOT EDIT! File to edit: ../dog-breeds.ipynb. | |
| # %% auto 0 | |
| __all__ = ['learn_inf', 'categories', 'image', 'label', 'examples', 'intf', 'classify_image'] | |
| # %% ../dog-breeds.ipynb 2 | |
| from fastai import * | |
| from fastai.vision.all import * | |
| import gradio as gr | |
| # %% ../dog-breeds.ipynb 13 | |
| # Load model wherever you plan to use it for inference | |
| learn_inf = load_learner('export2.pkl') | |
| # %% ../dog-breeds.ipynb 15 | |
| categories = ['Abyssinian', 'Bengal', 'Birman', 'Bombay', 'British_Shorthair', | |
| 'Egyptian_Mau', 'Maine_Coon', 'Persian', 'Ragdoll', 'Russian_Blue', | |
| 'Siamese', 'Sphynx', 'american_bulldog', 'american_pit_bull_terrier', | |
| 'basset_hound', 'beagle', 'boxer', 'chihuahua', 'english_cocker_spaniel', | |
| 'english_setter', 'german_shorthaired', 'great_pyrenees', 'havanese', | |
| 'japanese_chin', 'keeshond', 'leonberger', 'miniature_pinscher', | |
| 'newfoundland', 'pomeranian', 'pug', 'saint_bernard', 'samoyed', | |
| 'scottish_terrier', 'shiba_inu', 'staffordshire_bull_terrier', | |
| 'wheaten_terrier', 'yorkshire_terrier'] | |
| def classify_image(img): | |
| pred, idx, probs = learn_inf.predict(img) | |
| return dict(zip(categories, map(float,probs))) | |
| # %% ../dog-breeds.ipynb 16 | |
| image = gr.Image(shape=(192,192)) | |
| label = gr.Label() | |
| examples = ['dog.jpg', 'cat.jpg'] | |
| intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) | |
| intf.launch(inline=True, share=False) |