import streamlit as st from transformers import pipeline from PIL import Image import face_recognition import cv2 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)