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| import gradio as gr | |
| from fastai.vision.all import * | |
| import skimage | |
| from fastai.vision.all import PILImage | |
| import datetime | |
| learn = load_learner('model.pkl') | |
| labels = learn.dls.vocab | |
| def predict(img): | |
| img = PILImage.create(img) | |
| img = img.resize((512, 512)) | |
| pred, pred_idx, probs = learn.predict(img) | |
| if pred == "bicornis": | |
| filename = f"bicornis_{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}.jpg" | |
| img.save(filename) | |
| return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
| examples = ['image1.jpg', 'image2.jpg'] | |
| gr.Interface(fn=predict, inputs=gr.components.Image(), outputs=gr.components.Label(num_top_classes=2), examples=examples).launch() |