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Face detector/embeddings based on MTCNN, tensorflow and golang

Implementation based on . Tensorflow (1.4.1) and the golang binding are required.

Model file cmd/mtcnn.pb is converted from facenet too (see scripts/ You will need to add facenet/src to PYTHONPATH to use it). You may need to regenerate the model file for a different version of tensorflow.

The facenet protobuf model file is available for download (see instructions from facenet).


	// detection
	bs, err := ioutil.ReadFile(*imgFile)
	img, err := goface.TensorFromJpeg(bs)
	det, err := goface.NewMtcnnDetector("mtcnn.pb")
	bbox, err := det.DetectFaces(img) //[][]float32, i.e., [x1,y1,x2,y2],...

	// embeddings
	mean, std := goface.MeanStd(img)
	wimg, err := goface.PrewhitenImage(img, mean, std)
	fn, err := goface.NewFacenet("facenet.pb")
	emb, err := fn.Embedding(wimg)

See cmd/detect.go. Use go build to build the binary and run with --help.


  • Not exactly the same (e.g., nms/padding is depending on tensorflow implementation).
  • Not fully tested. Performance could a little bit worse.
  • Face landmark support not implemented.

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