# Import libraries
from fastai.vision.all import *
import gradio as gr

# Load model
learn = load_learner('labrador.pkl')

# Define categories
categories = ('Black', 'Golden')

# Define function to classify image
def classify_image(img):
	pred, idx, probs = learn.predict(img)
	return dict(zip(categories, map(float, probs)))

# Define Gradio interface
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ['black.png', 'golden.png', 'banana.jpg']

intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False)