CameraLiveFaceRecognition / backup.before.face.recognition.app.py
awacke1's picture
Rename app.py to backup.before.face.recognition.app.py
6d3ca86 verified
raw
history blame
4.29 kB
import streamlit as st
import cv2
import numpy as np
import datetime
import os
import time
import base64
import re
import glob
from camera_input_live import camera_input_live
# Set wide layout
st.set_page_config(layout="wide")
# Decorator for caching images
def get_image_count():
return {'count': 0}
# Function Definitions for Camera Feature
def save_image(image, image_count):
timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
filename = f"captured_image_{timestamp}_{image_count['count']}.png"
image_count['count'] += 1
bytes_data = image.getvalue()
cv2_img = cv2.imdecode(np.frombuffer(bytes_data, np.uint8), cv2.IMREAD_COLOR)
cv2.imwrite(filename, cv2_img)
return filename
def get_image_base64(image_path):
with open(image_path, "rb") as image_file:
return base64.b64encode(image_file.read()).decode()
# Function Definitions for Chord Sheet Feature
def process_line(line):
if re.search(r'\b[A-G][#b]?m?\b', line):
line = re.sub(r'\b([A-G][#b]?m?)\b', r"<img src='\1.png' style='height:20px;'>", line)
return line
def process_sheet(sheet):
processed_lines = []
for line in sheet.split('\n'):
processed_line = process_line(line)
processed_lines.append(processed_line)
return '<br>'.join(processed_lines)
# Main Function
def main():
# Layout Configuration
col1, col2 = st.columns([2, 3])
# Camera Section
with col1:
#st.markdown("πŸ“Ή Real-Time Camera Stream πŸš€")
#st.markdown("## πŸ‘οΈβ€πŸ—¨οΈ Eye on the World: Real-Time Camera Stream 🌐")
#st.markdown("πŸ”΄ Live Feed: Real-Time Camera Stream πŸŽ₯")
#st.markdown("🌟 Instant Vision: Real-Time Camera Stream πŸ“Έ")
#st.markdown("πŸ•΅οΈβ€β™‚οΈ Spy Mode: Real-Time Camera Stream πŸ•ΆοΈ")
#st.markdown("πŸš€ Explore Now: Real-Time Camera Stream 🌍")
#st.markdown("πŸ’‘ Illuminate: Real-Time Camera Stream πŸ”¦")
#st.markdown("πŸŒ‰ Views Unfold: Real-Time Camera Stream 🏞️")
st.markdown("✨ Magic Lens: Real-Time Camera Stream 🌈")
snapshot_interval = st.slider("Snapshot Interval (seconds)", 1, 10, 5)
image_placeholder = st.empty()
if 'captured_images' not in st.session_state:
st.session_state['captured_images'] = []
if 'last_captured' not in st.session_state:
st.session_state['last_captured'] = time.time()
image = camera_input_live()
if image is not None:
image_placeholder.image(image)
if time.time() - st.session_state['last_captured'] > snapshot_interval:
image_count = get_image_count()
filename = save_image(image, image_count)
st.session_state['captured_images'].append(filename)
st.session_state['last_captured'] = time.time()
sidebar_html = "<div style='display:flex;flex-direction:column;'>"
for img_file in st.session_state['captured_images']:
image_base64 = get_image_base64(img_file)
sidebar_html += f"<img src='data:image/png;base64,{image_base64}' style='width:100px;'><br>"
sidebar_html += "</div>"
st.sidebar.markdown("## Captured Images")
st.sidebar.markdown(sidebar_html, unsafe_allow_html=True)
# JavaScript Timer
st.markdown(f"<script>setInterval(function() {{ document.getElementById('timer').innerHTML = new Date().toLocaleTimeString(); }}, 1000);</script><div>Current Time: <span id='timer'></span></div>", unsafe_allow_html=True)
# Chord Sheet Section
with col2:
st.markdown("## 🎬 Action! Real-Time Camera Stream Highlights πŸ“½οΈ")
all_files = [f for f in glob.glob("*.png") if ' by ' in f]
selected_file = st.selectbox("Choose a Dataset:", all_files)
if selected_file:
with open(selected_file, 'r', encoding='utf-8') as file:
sheet = file.read()
st.markdown(process_sheet(sheet), unsafe_allow_html=True)
# Trigger a rerun only when the snapshot interval is reached
if 'last_captured' in st.session_state and time.time() - st.session_state['last_captured'] > snapshot_interval:
st.experimental_rerun()
if __name__ == "__main__":
main()