pip install toml

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



repo_id = "laaraap/anomaly-detection-using-autoencoders"

learner = from_pretrained_fastai(repo_id)
labels = learner.dls.vocab

# Definimos una función que se encarga de llevar a cabo las predicciones
def predict(img):
    #img = PILImage.create(img)
    pred = learner.predict(img)
    mse = np.mean((img - pred) ** 2)
    thresh = 0.02767541486024857
    if mse >= thresh:
      label = 'anomaly'
    else:
      label = 'not anomaly'
    return label
    
# Creamos la interfaz y la lanzamos. 
gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(128, 128)), outputs=label, examples=['uno.png','tres.png']).launch(share=False)