from fastai.vision.all import *
import gradio as gr
import skimage

learn = load_learner('pet_class_model_resnet18.pkl')

examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']

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))}

gr.Interface(fn=predict, 
             inputs=gr.inputs.Image(shape=(512, 512)), 
             outputs=gr.outputs.Label(num_top_classes=3),
             examples=examples,
             title="Pet Breed Classifier"
             ).launch(share=False)