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

learn = load_learner('guitars.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 = "Guitar Classifier"
examples = ['assets/Telecaster.jpg', 'assets/Les_Paul.jpg', 'assets/Stratocaster.jpg', 'assets/SG.jpg', 'assets/Flying_V.jpg', 'assets/Explorer.jpg']
interpretation='default'
enable_queue=True

interface = gr.Interface(fn=predict,inputs=gr.Image(type="pil"),outputs=gr.Label(num_top_classes=5),title=title,examples=examples)

interface.queue()

interface.launch()