import gradio as gr
from transformers import pipeline

from transformers import AutoFeatureExtractor, AutoModelForImageClassification

extractor = AutoFeatureExtractor.from_pretrained("kdhht2334/autotrain-diffusion-emotion-facial-expression-recognition-40429105176")
fer_model = AutoModelForImageClassification.from_pretrained("kdhht2334/autotrain-diffusion-emotion-facial-expression-recognition-40429105176")

pipe = pipeline(task="image-classification", 
                # model that can do 7-emotion classification
                model=fer_model)
gr.Interface.from_pipeline(pipe, 
                           title="7-emotion classification in DiffusionFER dataset",
                           description="Facial expression recognition trained with Transformer,
                           examples = ['happy.png', 'angry.png',],
                           article = "Author: <a href=\"https://huggingface.co/FER-Universe\">Daeha Kim</a>",
                           ).launch()