app.py

import streamlit as st
# from transformers import pipeline
from PIL import Image
import face_recognition
import cv2
import numpy as np
import requests
import os

st.title("AIMLJan24 - Face Recognition")

file_name = st.camera_input("Take a picture")  #st.file_uploader("Upload image  ")

if file_name is not None:
    col1, col2 = st.columns(2)

    image = Image.open(file_name)
    col1.image(image, use_column_width=True)

# pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")

# st.title("AIMLJan24 First App on Hugging face - Hot Dog? Or Not?")

# file_name = st.file_uploader("Upload the test image to find is this hot dog ! ")

# if file_name is not None:
#     col1, col2 = st.columns(2)

#     image = Image.open(file_name)
#     col1.image(image, use_column_width=True)
#     predictions = pipeline(image)

#     col2.header("Probabilities")
#     for p in predictions:
#         col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%")


# # my first app
# import streamlit as st

# x = st.slider('Select a value')
# st.write(x, 'squared is', x * x)