app.py

import gradio as gr
from fastai.vision.core import PILImage

import fastai.vision.all as fav
import os
if os.name != 'posix':
    print('Converting PosixPath to WindowsPath')
    import pathlib
    pathlib.PosixPath = pathlib.WindowsPath

def is_cat(x): return x[0].isupper()  # Used by model
learn = fav.load_learner('model.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))}

iface = gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3))

iface.launch()

# def greet(name):
#     return "Hello " + name + "!!"
#
# # iface = gr.Interface(fn=greet, inputs="text", outputs="text")
#
# iface.launch()