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Runtime error
| from fastai.vision.all import * | |
| import gradio as gr | |
| learn = load_learner("model.pkl") | |
| labels = learn.dls.vocab | |
| def classify_image(img): | |
| pred, idx, probs = learn.predict(img) | |
| return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
| image = gr.inputs.Image(shape=(192,192)) | |
| label = gr.outputs.Label() | |
| examples = [] | |
| for t in templates: | |
| for n in range(1,4): | |
| examples.append(f"campanelle/{n}.jpg") | |
| examples.append(f"macaroni/{n}.jpg") | |
| examples.append(f"fusilli/{n}.jpg") | |
| title = "Pasta Recognition" | |
| description = """ | |
| Pasta is delicious, but there are too many pasta types to remember. This app will help you | |
| recall the name of the pasta whose image you'll upload. | |
| Under the hood it's a pasta classifier, built using Fast.ai by fine-tuning the | |
| `convnext_base_in22ft1k` model. It supports only the followig pasta types: | |
| * Campanelle | |
| * Ditalini | |
| * Fettuccine | |
| * Fusilli | |
| * Linguine | |
| * Macaroni | |
| * Pappardelle | |
| The model's accuracy is ~82%. | |
| The notebook used to train the model can be seen [in Google Colab](https://colab.research.google.com/drive/1NM6BvRkV7xDlnncFqVRGxxg0GFtqpVgT?usp=sharing). | |
| """ | |
| iface = gr.Interface(fn=classify_image, inputs=image, outputs=gr.outputs.Label(), examples=examples, title=title, description=description) | |
| iface.launch(inline=False, share=True) | |