app.py

import torch
import streamlit as st
from transformers import pipeline

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("feature-extraction", model="minchul/cvlface_adaface_ir101_webface12m", trust_remote_code=True)

vis_feat = pipe("https://huggingface.co/datasets/nsvanirudh/test/resolve/main/VIS-frame-1653-used.png")
print(vis_feat)
st.write(vis_feat)
#feature_extractor(text,return_tensors = "pt")[0].numpy().mean(axis=0)

#st.write(x, 'squared is', x * x)