app.py

import numpy as np
import gradio as gr
from huggingface_hub import from_pretrained_fastai

learn = from_pretrained_fastai('mindwrapped/pokemon-card-checker')

def check_card(image):
    pred_label, _, scores = learn.predict(image)
    scores = scores.detach().numpy()
    return {'real': float(scores[1]), 'fake': float(scores[0])}


demo = gr.Interface(
  fn=check_card, 
  inputs="image",
  outputs="label",
  examples=['real-1.jpeg','real-2.jpeg','fake-1.jpeg','fake-2.jpeg','real-3.jpeg','real-4.jpeg','fake-3.jpeg','fake-4.jpeg'],
  title='Pokemon Card Checker',
  description='A resnet34 model fine-tuned to determine whether Pokemon cards are real or fake. Check out the dataset [here](https://www.kaggle.com/datasets/ongshujian/real-and-fake-pokemon-cards).\nCan you guess which cards are real and fake?\n\nI can\'t. :D [Card Labels](https://gist.github.com/mindwrapped/e5aad747757ef006037a1a1982be34fc)\n\nDataset created by [Shujian Ong](https://www.kaggle.com/ongshujian)\nSpace by [Scott Krstyen (mindwrapped)](https://huggingface.co/mindwrapped)',
  )

demo.launch()