Using python opencv to detect face and send the frames to FFmpeg to create HLS(HTTP Live Streaming)

face-detection.py

import numpy as np
import cv2
import sys

cap = cv2.VideoCapture(0)

face_cascade = cv2.CascadeClassifier('<PATH_TO_CASCADES_FOLDER>/haarcascade_frontalface_default.xml')

while(True):
    # Capture frame-by-frame
    ret, frame = cap.read()

    # Our operations on the frame come here
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    for (x, y, w, h) in faces:
        img = cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = img[y:y+h, x:x+w]

    # Print frame height width channels
    # height, width, channels = frame.shape
    # print height, width, channels

    framestring = frame.tostring()
    sys.stdout.write(framestring)

    # Display the resulting frame
    cv2.imshow('frame', frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()

generate_hls.sh

#!/bin/bash

# Create folder from args
mkdir -p $1

# Get into the folder
cd $1

# Start running FFmpeg HLS Live streaming
python face-detection.py | ffmpeg  \
  -f rawvideo \
  -pixel_format bgr24 \
  -framerate 10 \
  -video_size 1280x720 \
  -i - foo.mp4  \
  -vcodec libx264 \
  -acodec copy \
  -pix_fmt yuv420p \
  -color_range 2 \
  -hls_time 1 \
  -hls_list_size 5 \
  -hls_flags delete_segments \
  -use_localtime 1 \
  -hls_segment_filename '%Y%m%d-%s.ts' \
  ./playlist.m3u8