| import timm | |
| import gradio as gr | |
| from fastai.vision.all import * | |
| learn = load_learner('cat.pkl') | |
| labels = learn.dls.vocab | |
| def classify_image(img): | |
| img = PILImage.create(img) | |
| pred, pred_idx, probs = learn.predict(img) | |
| return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
| images = gr.inputs.Image(shape=(300, 300)) | |
| outputs = gr.outputs.Label(num_top_classes=3) | |
| examples = ['british-shorthair.jpg', | |
| 'maine-coon.jpg', 'european-shorthair.jpg'] | |
| interface = gr.Interface(fn=classify_image, inputs=images, | |
| outputs=outputs, examples=examples) | |
| interface.launch(inline=False) | |