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Runtime error
| # AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb. | |
| # %% auto 0 | |
| __all__ = ['learn', 'labels', 'examples', 'add_image_label', 'predict'] | |
| # %% app.ipynb 2 | |
| import timm | |
| from fastai.vision.all import * | |
| import gradio as gr | |
| def add_image_label(x): | |
| names = ["gond", "kalighat", "kangra", "madhubani", "mandana", "pichwai", "warli"] | |
| for name in names: | |
| if name in Path(x).name: | |
| return name | |
| elif "kerala" in Path(x).name: | |
| return "kerala mural" | |
| return "unknown" | |
| # %% app.ipynb 4 | |
| learn = load_learner("model.pkl") | |
| # %% app.ipynb 6 | |
| labels = learn.dls.vocab | |
| def predict(img): | |
| img = PILImage.create(img) | |
| pred,pred_idx,probs = learn.predict(img) | |
| return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
| # %% app.ipynb 8 | |
| examples = ["examples//warli.jpeg", "examples//madhubani.jpg"] | |
| gr.Interface(fn=predict, inputs=gr.Image(type="pil"), outputs=gr.Label(num_top_classes=3), examples = examples, title = "Indian Art Classifier").launch(inline=False, debug=True) | |