app.py

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

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 = "Breast cancer detection with Deep Transfer Learning(ResNet18)."
description = "Upload a breast X-ray image to detect potential issues."
article = "Web app built and managed by Addai Fosberg"
examples = ['img1.jpeg', 'img2.jpeg']

iface = gr.Interface(
    fn=predict,
    inputs=gr.Image(),
    outputs=gr.Label(num_top_classes=3),
    title=title,
    description=description,
    article=article,
    examples=examples,
    enable_queue=True
)

iface.launch()