from fastai.vision.all import load_learner
import gradio as gr
import os

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

learn = load_learner('model.pkl')

categories = ('Dog', 'Cat')

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

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

# put all images from the images folder into the examples list
examples = []
for file in os.listdir("images"):
    if file.endswith(".jpg"):
        examples.append("images/" + file)

iface = gr.Interface(fn=classify_image, inputs="image", outputs="label", examples=examples)
iface.launch()