from fastai.vision.all import *
import gradio as gr
learn = load_learner('export.pkl')


categories = ('broccoli', 'marijuana')


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


image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
ß
examples = ['broccoli.jpeg', 'marijuana.jpeg', 'brocc 2.jpeg',
            'weed 2.jpeg', 'brocc 3.jpeg', 'weed 3.jpeg', 'weed 4.jpeg']

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

intf.launch(inline=False)