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Version: 3.24.2

Face estimation

Estimation Processing Blocks​

  • GLASSES_ESTIMATOR estimates glasses presence on a face
  • AGE_ESTIMATOR estimates age
  • GENDER_ESTIMATOR estimates gender
  • EMOTION_ESTIMATOR estimates emotions
  • MASK_ESTIMATOR estimates mask precense
  • EYE_OPENNESS_ESTIMATOR estimates eye openness

Modifications and versions​

Modification Version Face SDK version Detection time CPU (ms)* Detection time GPU (ms)** Accuracy, (average error in years)
light13.19 1 2 5.5
2 1 2 4.9
heavy13.19 1 2 4.7
2 1 2 3.5
* - CPU Intel Xeon E5-2683 v4 (single-core)
** - GPU (NVIDIA GTX 10xx series)
note

The default modification is "heavy".

Processing Block specification​

  1. The input Context must contain an image in binary format and objects array from Face Detector and Face Fitter:

    Click here to expand the input Context specification
    {
        "image" : {
        "format": "NDARRAY",
            "blob": "data pointer",
            "dtype": "uint8_t",
            "shape": [height, width, channels]
        },
        "objects": [{
            "id": {"type": "long", "minimum": 0},
            "class": "face",
            "confidence": {"double",  "minimum": 0,  "maximum": 1},
            "bbox": [x1, y2, x2, y2]
            "keypoints": {
                "left_eye_brow_left":   {"proj" : [x, y]},
                "left_eye_brow_up":     {"proj" : [x, y]},
                "left_eye_brow_right":  {"proj" : [x, y]},
                "right_eye_brow_left":  {"proj" : [x, y]},
                "right_eye_brow_up":    {"proj" : [x, y]},
                "right_eye_brow_right": {"proj" : [x, y]},
                "left_eye_left":        {"proj" : [x, y]},
                "left_eye":             {"proj" : [x, y]},
                "left_eye_right":       {"proj" : [x, y]},
                "right_eye_left":       {"proj" : [x, y]},
                "right_eye":            {"proj" : [x, y]},
                "right_eye_right":      {"proj" : [x, y]},
                "left_ear_bottom":      {"proj" : [x, y]},
                "nose_left":            {"proj" : [x, y]},
                "nose":                 {"proj" : [x, y]},
                "nose_right":           {"proj" : [x, y]},
                "right_ear_bottom":     {"proj" : [x, y]},
                "mouth_left":           {"proj" : [x, y]},
                "mouth":                {"proj" : [x, y]},
                "mouth_right":          {"proj" : [x, y]},
                "chin":                 {"proj" : [x, y]},
                "points": ["proj": [x, y]]
            }
        }]
    }

    Example of Face Detector and Face Fitter is in Example of face detection and landmarks estimation].

  2. After calling the estimation Processing Block, each object from the "objects" array will be added attributes corresponding to this block.

    Specification of the output Context:

    [{
        "age": {"type": "long", "minimum": 0}
    }]

Example of working with the estimation processing block​

To evaluate facial attributes in an image, perform the following steps:

  1. Create a Context configuration container and specify the values "unit_type", "modification", "version", of the block you are interested in. An example of creating a processing block can be found on the here].

    Processing Block configurable parameters]

  2. Pass the container-context obtained after the processing blocks of face detection and fitter's detection work

  3. Call the evaluation processing block

  4. Get the result of the processing block

    auto configCtx = service->createContext();
    configCtx["unit_type"] = "AGE_ESTIMATOR";
    pbio::ProcessingBlock blockEstimator = service->createProcessingBlock(configCtx);

    //------------------
    // creation of Face Detection Processing Blocks, and Context container with binary image
    //------------------

    faceDetector(ioData);
    faceFitter(ioData);
    blockEstimator(ioData);

    long age = ioData["objects"][0]["age"].getLong();