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

learn = load_learner('export.pkl')

categories = ('grizzly','black','teddy')

def classify_image(img):
    pred,idx,probs = learn.predict(img)
    return dict(zip(categories, map(float,probs)))
	
image = "image"
label = "label"
examples = ['grizzly.jpg', 'black.jpg', 'teddy.jpg']

title = "Bear Classifier"
description = "A brear classifier trained on resnet18 dataset with fastai. "
interpretation='default'
enable_queue=True


intf = gr.Interface(fn=classify_image,
             inputs=gr.Image(height=512, width=512),
             outputs=gr.Label(num_top_classes=3),
             title=title,
             description=description,
             examples=examples).launch()