app.py

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

#installed the fastai
from fastai import *
from fastai.vision import *
#from fastbook import *

learn = load_learner('clasma.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 = "CLASMA"
description = "AI app for classifying disease in cereal crops leaves."
article = "sample image"
examples = ['corn.jpg']
interpretation = 'default'
enable_queue = True

gr.Interface(fn = predict, inputs = gr.inputs.Image(shape = (512, 512)),
outputs = gr.outputs.Label(num_top_classes = 8),
title = title,
description = description,
article = article,
examples = examples, 
interpretation = interpretation, 
enable_queue = enable_queue).launch()