Golang : Detect number of faces or vehicles in a photo
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 (
"fmt"
"github.com/lazywei/go-opencv/opencv"
"image"
gif "image/gif"
_ "image/jpeg"
_ "image/png"
"net/http"
"os"
)
// global variables
var (
cascade = new(opencv.HaarCascade)
)
func errCheck(err error) {
if err != nil {
panic(err)
}
}
func main() {
if len(os.Args) != 2 {
fmt.Printf("Usage : %s <imagefilename>\n", os.Args[0])
os.Exit(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)
errCheck(err)
defer imageFile.Close()
img, _, err := image.Decode(imageFile)
errCheck(err)
buffer := make([]byte, 512)
imageFile.Seek(0, 0) // reset reader
_, err = imageFile.Read(buffer)
errCheck(err)
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)
errCheck(err)
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.
References:
https://github.com/opencv/opencv/tree/master/data/haarcascades
http://stackoverflow.com/questions/25775650/golang-async-face-detection
See also : Golang : Surveillance with web camera and OpenCV
By Adam Ng
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