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

learner = load_learner('model.pkl')

categories = ('Kentish plover', 'White-faced plover')

def classify_images(img):
    pred, index, probs = learner.predict(img)
    return dict(zip(categories, map(float, probs)))
    # return {learner.dls.vocab[i]: float(probs[i]) for i in range(len(learner.dls.vocab))}

image = gr.Image()
# label = gr.outputs.Label()
examples = ['kentish.png', 'white-faced.png']

intf = gr.Interface(fn=classify_images, inputs=image, outputs='label', examples=examples)
intf.launch(inline=False)
# intface = gr.Interface(fn=classify_images, inputs=gr.inputs.Image(type='pil'),
#                        outputs=gr.outputs.Label(num_top_classes=2),
#                         title="Kentish plover vs White-faced plover Classifier",
#                         description="Upload an image of either Kentish plover and White-faced plover."
#                          )

# intface.launch(share=True)