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| # AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb. | |
| # %% auto 0 | |
| __all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image'] | |
| # %% app.ipynb 2 | |
| from fastai.vision.all import * | |
| import PIL | |
| import pathlib | |
| import gradio as gr | |
| def is_cat(x): return x[0].isupper() | |
| # %% app.ipynb 4 | |
| # Check if you are on a Windows system | |
| if sys.platform == 'win32': | |
| # Set the base PosixPath to WindowsPath | |
| pathlib.PosixPath = pathlib.WindowsPath | |
| pathlib.PosixPath | |
| # %% app.ipynb 5 | |
| learn =load_learner('cat_dog_model.pkl') | |
| # %% app.ipynb 7 | |
| categories= ('Dog', 'Cat') | |
| def classify_image(img): | |
| pred,idx, probs = learn.predict(img) | |
| return dict(zip(categories, map(float,probs))) | |
| # %% app.ipynb 9 | |
| image = gr.Image(height=192,width=192) | |
| label = gr.Label() | |
| examples =['dog.jpg', 'cats.jpeg', 'dogs.png'] | |
| intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) | |
| intf.launch(inline=False) | |