import gradio as gr
from fastai.vision.all import *
model_dir='model/'
learn = load_learner(model_dir+'jazzinstruments.pkl')

labels = learn.dls.vocab
labels
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 = "Jazz Instruments Classifer"
description = "A Jazz Instrument trained on a dataset create imagesearch : doublebasses, drumkits, guitars, saxophones, clarinettes"
article=""
examples = ["guitare.jpeg","double-bass.jpg","saxophone.jpeg"]
interpretation='default'
enable_queue=True

gr.Interface(fn=predict,
             inputs=gr.Image(type="pil"),
             outputs=gr.Label(num_top_classes=5),
             examples=["guitare.jpeg","double-bass.jpg","saxophone.jpeg"]).launch()