Person and Face Detection using Intel OpenVINO toolkit

People and Face Detection in Video for Security Surveillance using the Intel Distribution of OpenVINO toolkit.

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Person and Face Detection using Intel OpenVINO toolkit

Things used in this project

Software apps and online services

Intel OpenVINO™ toolkit

Python 3

Story

This project can be used to detect the presences of people in a room. It uses the pre-trained models downloaded using the OpenVINO model downloader.

Demonstration Video

This project can be used to detect the presence of people by detecting their faces and their body.

Steps

1 Download and install Anaconda Distribution of Python

2 Install all the dependencies

3 Download the Intel Distribution of OpenVINO toolkit.(My OpenVINO version - 2020.0.1.033)

Python Virtual Environment

1 Install virtual environment

pip install virtualenv

virtualenv --system-site-packages -p python openvinoenv

2 Activate virtual environment

openvinoenv\Scripts\activate

3 Running "setupvars.bat" file to set up the OpenVINO environment variables

cd "C:\Program Files (x86)\IntelSWTools\openvino_2020.1.033\bin\"setupvars.bat

4 Installing all the requirements from the "requirements.txt" file

cd "C:\Program Files (x86)\IntelSWTools\openvino_2020.1.033\deployment_tools\model_optimizer>"

pip install -r requirements.txt

5 Once done with OpenVINO, deactivate the environment

deactivate

NOTE - I have created a batch file named "openvinoenv.bat" to run the following steps in one singe line.

call "openvinoenv\Scripts\activate"call "C:\Program Files (x86)\IntelSWTools\openvino_2020.1.033\bin\setupvars.bat"

With a single line, the python virtual environment for OpenVINO toolkit can be created and the OpenVINO environment variables can be initialized.

openvinoenv.bat

Pre-trained Models

It uses the pre-trained models from the Intel OpenVino pre-trained models.

The following pre-trained models were downloaded using the model downloader

python "C:\Program Files (x86)\IntelSWTools\openvino\deployment_tools\open_model_zoo\tools\downloader\downloader.py"

face-detection-adas-0001 - link
person-detection-retail-0013 - link

Demonstration Videos used from the sample videos of intel-iot-devkit Github Repository.

System specifications used

Processor - Intel Core i7 9750H

Ram - 16 GB

OS - Windows 10 64 bit

Final Code Github Repository Link - here

Date of Download of Intel® Distribution of OpenVINO toolkit for Windows - January, 2020 (w_openvino_toolkit_p_2020.1.033.exe)

Email ID used- same as the one with the hackster.io

main.py

import cv2 

net2 = cv2.dnn.readNet('person-detection-retail-0013.bin', 'person-detection-retail-0013.xml')
net = cv2.dnn.readNet('face-detection-adas-0001.bin', 'face-detection-adas-0001.xml')

cap = cv2.VideoCapture("video1.mp4")

font = cv2.FONT_HERSHEY_SIMPLEX

while cv2.waitKey(1) < 0:
    hasFrame, frame = cap.read()
    frame = cv2.resize(frame,(1280,720),fx=0,fy=0, interpolation = cv2.INTER_CUBIC)
    if not hasFrame:
        break

    face_blob = cv2.dnn.blobFromImage(frame, size=(672, 384))
    net.setInput(face_blob)
    out_face = net.forward()

    for detection in out_face.reshape(-1, 7):
        confidence = float(detection[2])
        xmin = int(detection[3] * frame.shape[1])
        ymin = int(detection[4] * frame.shape[0])
        xmax = int(detection[5] * frame.shape[1])
        ymax = int(detection[6] * frame.shape[0])

        if confidence > 0.5:
            cv2.rectangle(frame, (xmin, ymin), (xmax, ymax), color=(0, 255, 0))
            cv2.putText(frame,'FACE',(xmin, (ymin-10)),font, 0.4,(0, 255, 255),1,cv2.LINE_AA) 

    person_blob = cv2.dnn.blobFromImage(frame, size=(672, 384))
    net2.setInput(person_blob)
    out_person = net2.forward()

    for detection in out_person.reshape(-1, 7):
        confidence2 = float(detection[2])
        xmin2 = int(detection[3] * frame.shape[1])
        ymin2 = int(detection[4] * frame.shape[0])
        xmax2 = int(detection[5] * frame.shape[1])
        ymax2 = int(detection[6] * frame.shape[0])

        if confidence2 > 0.6:
            cv2.rectangle(frame, (xmin2, ymin2), (xmax2, ymax2), color=(0, 255, 0))
            
            cv2.putText(frame,'PERSON',(xmin2, (ymin2-10)),font, 0.4,(0, 255, 255),1,cv2.LINE_AA) 
    cv2.imshow('OpenVINO face detection', frame)