people_counter

This application is designed to count the number of people and their duration in an environment. Its use cuts across different applications such as counting the number of people in a mall or using it to limit access of people to a place.

Demo video of running the app

Guide for running the app

Prerequisite

• Openvino (You can run this script to automate the installation of openvino)
• Nodejs and npm

Extracting the model

First, download the ssd_mobilenet_v2_coco model

From command line/terminal, navigate to the directory where the model was downloaded and extract it using

tar -xvf ssd_mobilenet_v2_coco_2018_03_29.tar.gz

Go to the just extracted directory (ssd_mobilenet_v2_coco_2018_03_29) and generate the intermediate represention (IR) files i.e.(.xml and .bin) using the model optimizer by running the following

python /opt/intel/openvino/deployment_tools/model_optimizer/mo_tf.py --input_model frozen_inference_graph.pb --tensorflow_object_detection_api_pipeline_config pipeline.config --tensorflow_use_custom_operations_config /opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/ssd_v2_support.json --reverse_input_channel

Clone this repo and create a "model" directory

Copy the generated .xml and .bin file into the "model" directory

From terminal, navigate to the cloned root directory and give permission to the script to install the required modules (i.e. nodejs, ffserver) for Mac and/or Linux with the following command

chmod +x setup.sh

Run the script using

./setup.sh

Running the App

Four terminal windows will be needed to run the app.

Start the Mosca Server on the first terminal window

cd <app_dir>/webservice/server/node-server
node ./server.js

If successful, the following message should appear

connected to ./db/data.db
Mosca server started.

Start the UI on the second terminal Window

Open new terminal (i.e. second terminal) and run the commands below

cd <app_dir>/webservice/ui
npm run dev

If successful, the following message should appear

webpack: Compiled successfully

Start the FFmpeg Server on the third terminal Window

Open the third terminal and run the commands below

cd <app_dir>
sudo ffserver -f ./ffmpeg/server.conf

Running the program on the fourth terminal

First, initialize the Openvino environment by running the command below

source /opt/intel/openvino/bin/setupvars.sh -pyver 3.5

To capture from video,

On the same terminal (i.e. the fourth terminal), run:

python3 main.py -i <location of video> -m model/frozen_inference_graph.xml -d CPU -pt 0.6 | ffmpeg -v warning -f rawvideo -pixel_format bgr24 -video_size 768x432 -framerate 24 -i - http://0.0.0.0:3004/fac.ffm

To capture from camera,

On the same terminal (i.e. the fourth terminal), run:

python3 main.py -i 0 -m model/frozen_inference_graph.xml -d CPU -pt 0.6 | ffmpeg -v warning -f rawvideo -pixel_format bgr24 -video_size 768x432 -framerate 24 -i - http://0.0.0.0:3004/fac.ffm

View Output

To see the output on a web based interface, open the link http://0.0.0.0:3004 in a browser.