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

learn = load_learner('export.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 = 'First Classifier'

description = 'Built with fastai'

examples = ['siamese.jpg']

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 , examples = examples , interpretation = interpretation , enable_queue = enable_queue).launch()