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| # AUTOGENERATED! DO NOT EDIT! File to edit: ../../lesson_2.ipynb. | |
| # %% auto 0 | |
| import gradio as gr | |
| __all__ = ['learn_inf', 'labels', 'title', 'description', 'article', | |
| 'examples', 'interpretation', 'enable_queue', 'predict'] | |
| # %% ../../lesson_2.ipynb 0 | |
| import fastai | |
| # %% ../../lesson_2.ipynb 1 | |
| import pandas | |
| # %% ../../lesson_2.ipynb 2 | |
| from fastai.vision.widgets import * | |
| # %% ../../lesson_2.ipynb 3 | |
| from fastai.vision.all import * | |
| # %% ../../lesson_2.ipynb 4 | |
| learn_inf = load_learner("./export.pkl") | |
| # %% ../../lesson_2.ipynb 6 | |
| labels = learn_inf.dls.vocab | |
| # %% ../../lesson_2.ipynb 7 | |
| def predict(img): | |
| img = PILImage.create(img) | |
| pred, pred_idx, probs = learn_inf.predict(img) | |
| return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
| # %% ../../lesson_2.ipynb 8 | |
| # %% ../../lesson_2.ipynb 9 | |
| title = "Car Classifier" | |
| description = "Upload the image of a car to get its type. The model uses the resnet18 trained on a variety of images of cars." | |
| article = "<p style='text-align: center'><a href='https://github.com/aar2dee2' target='_blank'>Made by aar2dee2</a></p>" | |
| examples = ['car2.jpeg', 'car3.jpeg', 'car4.jpeg', | |
| 'car5.jpg', 'car6.jpg', 'car7.jpg'] | |
| interpretation = 'default' | |
| enable_queue = True | |
| # %% ../../lesson_2.ipynb 10 | |
| gr.Interface( | |
| fn=predict, | |
| inputs=gr.inputs.Image(shape=(512, 512)), | |
| outputs=gr.outputs.Label(num_top_classes=3), | |
| title=title, | |
| description=description, | |
| article=article, | |
| examples=examples, | |
| interpretation=interpretation, | |
| enable_queue=enable_queue).launch() | |