app.py

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

learner = load_learner('dermatologist_fastai.pkl')
categories = (
    'acne_vulgaris',
 'actinic_keratosis',
 'allergic_contact_dermatitis',
 'dermatofibroma',
 'drug_induced_pigmentary_changes',
 'granuloma_annulare',
 'hidradenitis',
 'kaposi_sarcoma',
 'melanoma',
 'necrobiosis_lipoidica',
 'nematode_infection',
 'neutrophilic_dermatoses',
 'photodermatoses',
 'psoriasis',
 'sarcoidosis',
 'xeroderma_pigmentosum'
)

def predict(img):
    preds, idx, probs = learner.predict(img)
    return dict(zip(categories, map(float, probs)))  

def greet(name):
    return "Hello " + name + "!!"

image = gr.Image()
label = gr.Label()


demo = gr.Interface(fn=predict, inputs=image, outputs=label)
demo.launch(inline=False, share=True)