import gradio as gr
from fastbook import *
from fastai.vision.widgets import *


learn_inf = load_learner('numsimple.pkl')

def classify_image(img):
    pred, idx, probs = learn_inf.predict(img)
    categories = learn_inf.dls.vocab
    return { c: val for c,val in zip(categories,
                                     map(float, probs))
                   if val >= 0.05 }

# classify_image(xx)

image = gr.inputs.Image(shape=(224,244))
label = gr.outputs.Label()
#examples = ['/kaggle/input/images-2023-04-26/four.png']
worker = gr.Interface(fn=classify_image,
                    inputs=image,
                    outputs=label
                      #,
#                    examples=examples
                      )
worker.launch()