from fastai.vision.all import *
import gradio as gr
from PIL import Image
import numpy as np
from fastai.vision.core import PILImage

def is_cat(x): return x[0].isupper()

learn = load_learner('model.pkl')

categories = ('Dog','Cat')

def classify_image(img):
    if isinstance(img, np.ndarray):
        img = Image.fromarray(img.astype('uint8'), 'RGB')
    if not isinstance(img, PILImage):
        img = PILImage.create(img)
    pred,idx,probs=learn.predict(img)
    return dict(zip(categories,map(float,probs)))

image = gr.Image(width=192, height=192)
label = gr.Label()
examples = ['dog.jpg','cat.jpg','dog-cat.jpg']

intf= gr.Interface(fn=classify_image,inputs=image,outputs=label,examples=examples)
intf.launch(inline=False)