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from fastai.vision import *
import gradio as gr
from fastbook import *
import os
import glob
def classify_digit_type(img):
name = os.path.basename(os.path.normpath(img))
return name[0]
learn = load_learner('model.pkl')
categories = ('0', '1', '2', '3', '4', '5', '6', '7', '8', '9')
labels = learn.dls.vocab
def predict(img):
img = PILImage.create(img)
pred,pred_idx,probs = learn.predict(img)
return {labels[i]: float(probs[i]) for i in range(len(labels))}
gr.Interface(fn=predict, inputs=gr.Image(shape=(512, 512)), outputs=gr.Label(num_top_classes=3)).launch(share=False)