Hi there, is it possible to print/output the Facial Coordinates/Pupil Localization pointers in the JSON file with -json itself? Or any work around for the same?

or any other way to print the exact coordinates of the pupils or the other facial features?

This particular line is a possible (an in fact, experienced) infinite loop:

https://github.com/esimov/pigo/blob/0110acf7753778761ddd7b2ac4659de1c65b9c4b/core/pigo.go#L246

I've figured it out from the stack trace:

github.com/esimov/pigo/core.(*Pigo).classifyRegion(0xc0001a40a0, 0x42, 0x36, 0x9, 0xc00068e000, 0x238c, 0x238c, 0x5b, 0xbf800000)

The gorutine track trace parameters are as follows:

• 0xc0001a40a0 (the receiver)
• 0x42 row (constantly modified)
• 0x36 col (constantly modified)
• 0x9 scale (!!does not change!!)
• other params (do not change)

The issue comes from a rounding /casting error. The main readme (as well as my code) sets the cascade parameters scale factor as 1.1. When the scale is 9, the factor would come up with 9.9, which again becomes 9 because of the int() conversion.

The particular issue is that the source image was 91x100 (don't even ask), and I've calculated the face min/max size as 10% and 50% of the image width respectively. The minimum face size thus becomes 9 and with the scale ratio of 1.1 = infinite loop.

Possible fixes:

• Clamp the minimum value for a face size where it wouldn't cause problems (10px)
• Better main loop for this stuff to avoid rounding errors

Would it be possible to extend this library or use it as-is to perform facial recognition and thus identity of persons in images? (as opposed to face detection)

Hi there, I try to exec demo with Python 3.9 on Windows, sometimes got unexpected exit, with code -1073741819 (0xC0000005) , that err from C shared lib I think, and that because of index out of range usually. I'm not good at Golang and not founded the true reason from code, give me some advice to fix it please, thx.

Hi. I'm trying to implement webcam based facial motion capture with with library.

The current set of face and retina landmarks is quite good, but I'm wondering if it's possible to extend the landmark regions that the PICO process can identify.

Specifically:

Option 1: adding new face landmarks

I'm assuming that new facial landmark locations would require defining new cascade files. Did the paper authors mentioned any recommendations on collecting and tagging example training data, or the training process itself?

Option 2: adding simple paint based landmarks

Perhaps a simpler option would be to somehow define cascades for recognizing simple shapes like dot marks, or cross marks placed in an actor's face where the missing facial landmark points are needed.

Let me know if I missed anything.

Thanks!

Resources

AutoDesk SoftImage - The Motion Capture Process

I was wondering if this library can be used for detecting blinks.

You have a real-time example using python. Since chrome now supports (experimental) shape detection and video camera access: https://paul.kinlan.me/face-detection/ & https://medium.com/@joomiguelcunha/lets-play-with-chrome-s-face-detection-api-ca13017a958f I was wondering if using your WASM port it was able to detect if a face was blinking.

I'm developing a CCTV face detection app to send frame with good enough face detection quality (qTresh from example) to my backend site with employee face recognition capabilities. Nothing's wrong with Pigo and everything work as expected of this GODLY portable pure-go face-detection pkg. But I'm sort of stucked with some latency problem due to high fps (amount of frames) that the app need to "detect" with Pigo. I tried to decrease the FPS of the video reading to 10 fps but the latency still can't catch up to the video frames send by the CCTV.

Please help me if you got any tips or recommendation as a CLEARLY more experienced devs ^^.

I'm using Pigo 1.4.6.

Here's my code:

package main

import (
	"io"
	"io/ioutil"
	"log"
	"os"
	"time"

	pigo "github.com/esimov/pigo/core"
	"github.com/fogleman/gg"
	"github.com/unixpickle/ffmpego"
)

var f *os.File
var dc *gg.Context

func videoFileFacetest() {
	cascadeFile, err := ioutil.ReadFile("./cascade/facefinder")
	if err != nil {
		log.Fatalf("Error reading the cascade file: %v", err)
	}

	vr, _ := ffmpego.NewVideoReaderResampled("sample2.mp4", 10)
	// vw, _ := ffmpego.NewVideoWriter("output.mp4", vr.VideoInfo().Width, vr.VideoInfo().Height, 10)
	i := 0
	for {
		i++
		frame, err := vr.ReadFrame()
		if err == io.EOF {
			break
		}
		start := time.Now()
		pixels := pigo.RgbToGrayscale(frame)

		cols, rows := frame.Bounds().Max.X, frame.Bounds().Max.Y

		cParams := pigo.CascadeParams{
			MinSize:     20,
			MaxSize:     1000,
			ShiftFactor: 0.1,
			ScaleFactor: 1.1,

			ImageParams: pigo.ImageParams{
				Pixels: pixels,
				Rows:   rows,
				Cols:   cols,
				Dim:    cols,
			},
		}

		pigoFunc := pigo.NewPigo()
		classifier, err := pigoFunc.Unpack(cascadeFile)
		if err != nil {
			log.Fatalf("Error reading the cascade file: %s", err)
		}
		angle := 0.0 // cascade rotation angle. 0.0 is 0 radians and 1.0 is 2*pi radians

		// Run the classifier over the obtained leaf nodes and return the detection results.
		// The result contains quadruplets representing the row, column, scale and detection score.
		dets := classifier.RunCascade(cParams, angle)
		// // Calculate the intersection over union (IoU) of two clusters.

		// print(len(dets))
		// print("_")
		// println(len(dets2))

		var qTresh float32
		qTresh = 6.8
		goodQ := []pigo.Detection{}
		for i := range dets {
			if dets[i].Q > qTresh {
				goodQ = append(goodQ, dets[i])
			}
		}
		if len(goodQ) > 0 {
			dets2 := classifier.ClusterDetections(goodQ, 0.01)
			if len(dets2) > 0 {
				// dc = gg.NewContext(cols, rows)
				// dc.DrawImage(frame, 0, 0)

				for i := 0; i < len(dets2); i++ {
					if dets2[i].Q > qTresh {
						println("we got a winner here")
						// dc.DrawRectangle(
						// 	float64(dets2[i].Col-dets2[i].Scale/2),
						// 	float64(dets2[i].Row-dets2[i].Scale/2),
						// 	float64(dets2[i].Scale),
						// 	float64(dets2[i].Scale),
						// )

						// dc.SetLineWidth(20.0)
						// dc.SetStrokeStyle(gg.NewSolidPattern(color.RGBA{R: 255, G: 0, B: 0, A: 255}))
						// dc.Stroke()

						// vw.WriteFrame(dc.Image())
					}
				}
			}
		}
		elapsed := time.Since(start)
		log.Printf("Loop took %s", elapsed)
	}

	vr.Close()
	// vw.Close()
	return
}

func main() {
	videoFileFacetest()
}

Here's the sample video:

https://www.pexels.com/video/people-going-in-and-out-of-the-royal-opera-house-1721303/

Describe the bug

-fplc flag doesn't seem to work if -plc isn't specified.

This command works fine: $ pigo -in image.jpg -out output.jpg -cf ../pigo/cascade/facefinder -plc ../pigo/cascade/puploc -flpc ../pigo/cascade/lps

But running the following only detects the face but not its facial landmarks: $ pigo -in image.jpg -out output.jpg -cf ../pigo/cascade/facefinder -flpc ../pigo/cascade/lps

Expected behavior

-flpc should work without -plc as per the screenshot https://user-images.githubusercontent.com/883386/66802771-3b0cc880-ef26-11e9-9ee3-7e9e981ef3f7.png

my demo is : https://github.com/Taoja/web-wasm-faceDetector

there have two problems:

• the func rgbaToGrayscale is useless, the picture still colorful when i output imageData and use canvas render it
• unable detect face, maybe it is because func rgbaToGrayscale is useless

Hi there! I'm trying to pass the values for the eyes separately using the blinkdet example, but seems like it outputs the values for both the eyes together and not separately (just outputting max_radius)

Is there a way to output the values that I get using -json via a particular variable or just output the values (max_radius) of both the eyes separately?

Hi,

If I run your web example than I get this error: 2020/04/24 21:51:38 [ERROR] reading next part multipart: NextPart: EOF I must admit that I don't meet the requirements for this example. My python is python3 and my opencv is 4.2. OS is Ubuntu 20.04LTS. I tested as follows

1. Run: go run main.go -cf "../../cascade/facefinder"
2. Open URL: localhost:8081/cam in browser
3. Then this error appears Any ideas? Thanks

First off, just want to appreciate and thank you for this cool project you're working on. I was wondering if you could add the feature to compare two faces and describe how likely they are.