Published April 12, 2020

Human Face Detection

Human Face Detection application for Artificial Intelligence Applications using Jetson Nano Edge Computing Devises.

IntermediateShowcase (no instructions)3 hours1,053

Things used in this project

Hardware components

NVIDIA Jetson Nano Developer Kit

Webcam, Logitech® HD Pro

Software apps and online services

.NET nanoFramework Visual Studio extension

Story

This is a Human Face Detection application designed and deployed in Edge Computing Devise - Jetson Nano. This application can be used for various purpose in commercial establishments, airport security, shopping mall vigilance etc.

Face Detection Python Code

import cv2
print(cv2.__version__)
dispW=640
dispH=480
flip=2

#camSet='nvarguscamerasrc !  video/x-raw(memory:NVMM), width=3264, height=2464, format=NV12, framerate=21/1 ! nvvidconv flip-method='+str(flip)+' ! video/x-raw, width='+str(dispW)+', height='+str(dispH)+', format=BGRx ! videoconvert ! video/x-raw, format=BGR ! appsink'
#cam= cv2.VideoCapture(camSet)

cam=cv2.VideoCapture(1)
face_cascade=cv2.CascadeClassifier('/home/anbu/Desktop/PyPro/cascade/face.xml')

while True:
    ret, frame = cam.read()
    gray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
    faces=face_cascade.detectMultiScale(gray,1.3,5)
    for (x,y,w,h) in faces:
        cv2.rectangle(frame, (x,y),(x+w,y+h),(0,0,255),4)
    
    cv2.imshow('nanoCam',frame)
    cv2.moveWindow('nanoCam',0,0)
    if cv2.waitKey(1)==ord('q'):
        break
        
cam.release()
cv2.destroyAllWindows()