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

learn = load_learner('export.pkl')
categories = ('Big Truck','Bus','Car','Military Vehicle',
             'Motorcycle','Pickup truck','Van')

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

examples = []
path = Path('Test')
if path.exists():
    for img in path.glob('**/*.jpg'):
        examples.append(str(img))

image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()

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