app.py

__all__ = ['learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']

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

learn = load_learner('export.pkl')
#export.pkl is the name of the neural network file, change accordingly

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

image=gr.Image(height = 300, width = 300)
label = gr.Label()
examples = ['Cuts_for_nn.jpeg', 'Fracture_examp.jpeg', 'Rash.jpeg', 'Splinter_examp.jpeg', 'Splinter_download.jpeg', 'Cut_download.jpeg', 'Rash_download.jpeg', 'Fracture_download.jpeg']
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False)