| import gradio as gr | |
| from fastai.vision.all import * | |
| import skimage | |
| learn = load_learner('dog_breed.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 = "Doge Breed Classifier" | |
| description = "A dog breed classifier trained on duckduckgo images with fastai." | |
| 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, | |
| interpretation=interpretation, | |
| enable_queue=enable_queue | |
| ).launch() |