Multi Camera Multi Person Python* Demo

This demo demonstrates how to run Multi Camera Multi Person demo using OpenVINOTM.

How It Works

The demo expects the next models in the Intermediate Representation (IR) format:

It can be your own models or pre-trained model from OpenVINO Open Model Zoo. In the models.lst are the list of appropriate models for this demo that can be obtained via Model downloader. Please see more information about Model downloader here.

As input, the demo application takes:

The demo workflow is the following:

  1. The demo application reads tuples of frames from web cameras/videos one by one. For each frame in tuple it runs person detector and then for each detected object it extracts embeddings using re-identification model.
  2. All embeddings are passed to tracker which assigns an ID to each object.
  3. The demo visualizes the resulting bounding boxes and unique object IDs assigned during tracking.


Installation of dependencies

To install required dependencies run

pip3 install -r requirements.txt

Command line arguments

Run the application with the -h option to see the following usage message:

usage: [-h] -i I [I ...] -m M_DETECTOR
[--t_detector T_DETECTOR]
--m_reid M_REID
[--output_video OUTPUT_VIDEO]
[--config CONFIG]
[--history_file HISTORY_FILE]
Multi camera multi person tracking live demo script
optional arguments:
-h, --help show this help message and exit
-i I [I ...] Input sources (indexes of cameras or paths to video
-m M_DETECTOR, --m_detector M_DETECTOR
Path to the person detection model
--t_detector T_DETECTOR
Threshold for the person detection model
--m_reid M_REID Path to the person reidentification model
--output_video OUTPUT_VIDEO
--config CONFIG
--history_file HISTORY_FILE
-d DEVICE, --device DEVICE
MKLDNN (CPU)-targeted custom layers.Absolute path to a
shared library with the kernels impl.
--no_show Optional. Don't show output

Minimum command examples to run the demo:

# videos
python \
-i path/to/video_1.avi path/to/video_2.avi \
-d path/to/person-detection-retail-0013.xml \
-r path/to/person-reidentification-retail-0076.xml \
# web-cameras
python \
-i 0 1 \
-d path/to/person-detection-retail-0013.xml \
-r path/to/person-reidentification-retail-0076.xml \

Demo Output

The demo displays bounding boxes of tracked objects and unique IDs of those objects. To save output video with the result please use the option --output_video, to change configuration parameters please open the file and edit it.

Also demo can dump resulting tracks to a json file. To specify the file use the --history_file argument.