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

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

learn = load_learner('model.pkl')

categories = ['Dog', 'Cat']

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

image = gr.components.Image(type="pil", height=224, width=224)
label = gr.components.Label(num_top_classes=3)
examples = ['cat.jpg', 'dog.jpg', 'dunno.jpg']




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