A real-time object recognition application using Google's TensorFlow Object Detection API and OpenCV.

1. conda env create -f environment.yml
2. python object_detection_app.py / python object_detection_multithreading.py Optional arguments (default value):
   • Device index of the camera --source=0
   • Width of the frames in the video stream --width=480
   • Height of the frames in the video stream --height=360
   • Number of workers --num-workers=2
   • Size of the queue --queue-size=5
   • Get video from HLS stream rather than webcam '--stream-input=http://somertmpserver.com/hls/live.m3u8'
   • Send stream to livestreaming server '--stream-output=--stream=http://somertmpserver.com/hls/live.m3u8'

pytest -vs utils/ 

• Anaconda / Python 3.5
• TensorFlow 1.2
• OpenCV 3.0

• OpenCV 3.1 might crash on OSX after a while, so that's why I had to switch to version 3.0. See open issue and solution here.
• Moving the .read() part of the video stream in a multiple child processes did not work. However, it was possible to move it to a separate thread.

See LICENSE for details. Copyright (c) 2017 Dat Tran.