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Streamlit_cam.py
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Streamlit_cam.py
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import streamlit as st
import streamlit.components.v1 as components
import cv2
import logging as log
import datetime as dt
from time import sleep
cascPath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascPath)
log.basicConfig(filename='webcam.log',level=log.INFO)
video_capture = cv2.VideoCapture(0)
anterior = 0
# Streamlit begins
# Title
st.title("Face Detection application by Shreya Prasad")
st.header("A Python Face Detection App built using Streamlit")
# Building a sidebar
st.sidebar.subheader("Profile details")
t1 = st.sidebar.text_input("Name of the Person 1")
s1 = st.sidebar.slider("Age of the person 1")
st.sidebar.markdown("---")
st.sidebar.subheader("Profile details")
t2 = st.sidebar.text_input("Name of the Person 2")
s2 = st.sidebar.slider("Age of the person 2")
st.write("Name: ",t1)
st.write("Age: ", s1) # taking data from the sidebar
st.write("Name: ",t2)
st.write("Age: ", s2) # taking data from the sidebar
# Selection box
# first argument takes the titleof the selectionbox second argument takes options
How_is_streamlit = st.selectbox("likings: ",['Incredible', 'Good', 'Needs Improvement', 'Unsatisfactory'])
st.write("Your review is: ", How_is_streamlit)
st.markdown(f'<hr style="height:2px;border:none;color:#333;background-color:#333;" />', unsafe_allow_html=True)
st.header("Start Face Detection")
if st.button("Click here for face detection"):
while True:
if not video_capture.isOpened():
print('Unable to load camera.')
sleep(5)
pass
# Capture frame-by-frame
ret, frame = video_capture.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30)
)
# Draw a rectangle around the faces
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
if anterior != len(faces):
anterior = len(faces)
log.info("faces: " + str(len(faces)) + " at " + str(dt.datetime.now()))
# Display the resulting frame
cv2.imshow('Video', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# Display the resulting frame
cv2.imshow('Video', frame)
# When everything is done, release the capture
video_capture.release()
cv2.destroyAllWindows()