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

learn = load_learner('export.pkl')

categories = ('Benign', 'Malignant')

def classify_image(img):
    pred,idx,probs = learn.predict(img)
    return dict(zip(categories, map(float,probs)))

image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = ['Benign1.jpg','Benign2.jpg','Benign3.jpg', 'Malignant1.jpg', 'Malignant2.jpg', 'Malignant3.jpg']
title = 'Skin Cancer Predictor'
description = 'This app predicts whether skin cancer is benign or malignant. For reference only.'
article = "Author: <a href=\"https://huggingface.co/archietram\">Archie Tram</a>. "

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