Golang : Detect number of faces or vehicles in a photo

Tags : golang openCV detect-objects-number detect-faces detect-vehicles

This is a short tutorial on how to use OpenCV to detect the number of faces in an image. Knowing the number of faces in a given photo is crucial in developing machine learning capabilities that involve computer vision.

For examples,

1) A robot needs to know how many people to serve glasses of water.

2) A driverless car needs to know how many incoming cars and number of passengers in the car. IF the drive seat position has a face, chances are the incoming car is in motion.

In this example, we will learn how to detect the number of human faces with a command line Golang program and report the number. If you're looking to detect cars, use the HAAR cascade file for vehicle detection or download the XML files at https://github.com/abhi-kumar/CAR-DETECTION/blob/master/checkcas.xml or http://cogcomp.cs.illinois.edu/Data/Car/

If you need to detect more specific data such as eyes, ears, etc. Use the cascade files at https://github.com/opencv/opencv/tree/master/data/haarcascades.

Here you go!

 package main

 import (
 gif "image/gif"
 _ "image/jpeg"
 _ "image/png"

 // global variables
 var (
 cascade = new(opencv.HaarCascade)

 func errCheck(err error) {

 if err != nil {

 func main() {

 if len(os.Args) != 2 {
 fmt.Printf("Usage : %s <imagefilename>\n", os.Args[0])

 imageFileName := os.Args[1]

 fmt.Println("Analyzing [" + imageFileName + "]......")

 // we will use Go's method of load images
 // instead of openCV.LoadImage
 // because we want to detect if the user supplies animated GIF or not
 imageFile, err := os.Open(imageFileName)


 defer imageFile.Close()

 img, _, err := image.Decode(imageFile)

 buffer := make([]byte, 512)
 imageFile.Seek(0, 0) // reset reader
 _, err = imageFile.Read(buffer)

 filetype := http.DetectContentType(buffer)
 // check if image is GIF and if yes, check to see if it is animated GIF by
 // counting the LoopCount number
 fmt.Println("Analyzing image type : ", filetype)

 if filetype == "image/gif" {
 imageFile.Seek(0, 0)
 // warn if image is animated GIF
 gif, err := gif.DecodeAll(imageFile)
 if gif.LoopCount != 0 {
 fmt.Println("Animated gif detected. Will only scan for faces in the 1st frame.")

 // for vehicles XML files
 // see https://github.com/abhi-kumar/CAR-DETECTION/blob/master/checkcas.xml
 // or http://cogcomp.cs.illinois.edu/Data/Car/
 cascade = opencv.LoadHaarClassifierCascade("./haarcascade_frontalface_alt.xml")
 defer cascade.Release()

 // convert Go's image.Image type to OpenCV's IplImage(Intel Image Processing Library)
 openCVimg := opencv.FromImage(img)
 defer openCVimg.Release()

 if openCVimg != nil {
 faces := cascade.DetectObjects(openCVimg)
 fmt.Printf("Detected [%v] faces in image.\n", len(faces)) // <------- here !

 } else {
 panic("OpenCV FromImage error")


Sample output:

./detectfaces input.gif

Analyzing [input.gif]......

Analyzing image type : image/gif

Detected 1 faces in image.

./detectfaces img.gif

Analyzing [img.gif]......

Analyzing image type : image/gif

Animated gif detected. Will only scan for faces in the 1st frame.

Detected [0] faces in image.





  See also : Golang : Surveillance with web camera and OpenCV

Tags : golang openCV detect-objects-number detect-faces detect-vehicles

By Adam Ng

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