app.py

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

learn_inf = load_learner('model.pkl')

categories = ("Decease", "Healthy")

def classify(img):
    pred, pred_idx, probs = learn_inf.predict(img)
    return dict(zip(categories, map(float, probs)))

image = gr.inputs.Image(shape=(224, 224))
label = gr.outputs.Label()
examples = glob("*.jpg")

title = "Strawberry Leaves Decease Classifier"
description = "This classifier was trained on the ['Image Dataset for Tipburn Disorder Detection in Strawberry Leaves'](https://data.mendeley.com/datasets/trwfmgjjr6/1) and it is designed to help you detect weather straberry leaves are infected or not."
interpretation='default'

iface = gr.Interface(fn=classify, inputs=image, outputs=label, examples=examples, 
                     title=title, description=description, interpretation=interpretation)
iface.launch(enable_queue=True)