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Runtime error
Runtime error
| from fastai.vision.all import * | |
| import gradio as gr | |
| def is_cat(x): return x[0].isupper() | |
| learn = load_learner('./image_model.pkl') | |
| 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))} | |
| # All Gradio interfaces are created by constructing a gradio.Interface() object | |
| # The Interface() object takes in the function that we want to make an | |
| # interface for (usually an ML model inference function) | |
| # 'inputs' components (the number of input components should match | |
| # the number of parameters of the provided function) | |
| # 'outputs' components (the number of output components should match | |
| # the number of values returned by the provided function) | |
| title = "Dog Cat Classifier" | |
| description = "A dog cat classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces." | |
| article="<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Blog post</a></p>" | |
| examples = ['./cats_1.jpeg'] | |
| interpretation='default' | |
| enable_queue=True | |
| 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() | |