| import gradio as gr | |
| from fastai.vision.all import * | |
| import skimage | |
| learn = load_learner('export.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))} | |
| title = "Bear Classifier" | |
| description = "A classifier that differentiates between grizzly, black, and teddy bears." | |
| examples = [f'examples/{bear_type}.jpg' for bear_type in {'grizzly', 'black', 'teddy'}] | |
| queue_size = 20 | |
| demo = gr.Interface( | |
| fn=predict, | |
| inputs=gr.Image(width=512, height=512), | |
| outputs=gr.Label(num_top_classes=3), | |
| title=title, | |
| description=description, | |
| examples=examples | |
| ) | |
| demo.queue(max_size=queue_size) | |
| demo.launch() | |