Ottermad/pet-classifier

1import gradio as gr2from fastai.vision.all import *3import skimage4 5def label_func(x): 6    return x.parent.name7 8learn = load_learner('model (2).pkl')9 10labels = learn.dls.vocab11 12def predict(img):13    img = PILImage.create(img)14    pred,pred_idx,probs = learn.predict(img)15    return {labels[i]: float(probs[i]) for i in range(len(labels))}16 17title = "MNIST"18description = "Fast.ai Lesson 2"19interpretation='default'20enable_queue=True21 22gr.Interface(23    fn=predict,24    inputs=gr.inputs.Image(shape=(28, 28)),25    outputs=gr.outputs.Label(num_top_classes=10),26    title=title,27    description=description,28    interpretation=interpretation,29    enable_queue=enable_queue30).launch()31