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


categories = ('Arch','Cantilever','Suspension')


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()

examples = ['arch bridge 1.jpeg', 'arch bridge 2.jpeg','cantilever bridge 1.jpeg','cantilever bridge 2.jpeg','suspension bridge 1.jpeg','suspension bridge 2.webp']

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

intf.launch(inline=False)