| from fastai.vision.all import * | |
| learn = load_learner('orange_cats.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))} | |
| import gradio as gr | |
| title = "Cat, croissant, leaves, or yellow tiles?" | |
| description = "This model can classify images into 4 categories: cat, croissant, leaves, or yellow tiles. Upload an image or click an example image to test the model." | |
| examples =['examples/cat.jpg', 'examples/Croissant.png', 'examples/leaves.jpg', 'examples/Tiles.jpg'] | |
| gr.Interface(fn=predict,examples=examples, title=title,description=description,inputs=gr.Image(), outputs=gr.Label(num_top_classes=3)).launch(share=True) | |