Enable Face and Face Attribute Recognition

FindFace Multi allows you to recognize human faces and face attributes. Subject to your needs, you can enable recognition of such face attributes as age, gender, emotions, beard, glasses, medicine masks, head position, or liveness.

Face and face attribute recognition can be automatically enabled and configured during the FindFace Multi installation. If you skipped this step, you can manually do it later. Face and face attribute recognition works on both GPU- and CPU-acceleration.

Face object recognition is enabled by default. In case you removed face as a recognition object during the installation, you can add it later by following the below steps. If face object recognition is already installed, and you only need to enable face attribute recognition, jump to the steps 1.5, 1.6 and 4.1, 4.2. Other steps should be skipped.

To enable face recognition, do the following:

Specify neural network models for face object detection in the /opt/findface-multi/configs/findface-extraction-api/findface-extraction-api.yaml configuration file.

Important

Be sure to choose the right acceleration type for each model, matching the acceleration type of findface-extraction-api: CPU or GPU. Be aware that findface-extraction-api on CPU can work only with CPU-models, while findface-extraction-api on GPU supports both CPU- and GPU-models.

Open the findface-extraction-api.yaml configuration file.

sudo vi /opt/findface-multi/configs/findface-extraction-api/findface-extraction-api.yaml

Specify the face detector model in the detectors -> models section by pasting the following code:

GPU

detectors:

  ...
  models:
    ...
    face_jasmine:
      aliases:
      - face
      - nnd
      - cheetah
      model: detector/face.jasmine_fast.003.gpu.fnk
      options:
        min_object_size: 32
        resolutions:
        - 256x256
        - 384x384
        - 512x512
        - 768x768
        - 1024x1024
        - 1536x1536
        - 2048x2048

  ...

CPU

detectors:

  ...
  models:
    ...
    face_jasmine:
      aliases:
      - face
      - nnd
      - cheetah
      model: detector/face.jasmine_fast.003.cpu.fnk
      options:
        min_object_size: 32
        resolutions:
        - 256x256
        - 384x384
        - 512x512
        - 768x768
        - 1024x1024
        - 1536x1536
        - 2048x2048

  ...

Make sure that the objects -> face section contains the quality_attribute: face_quality and the base_normalizer: facenorm/crop2x.v2_maxsize400.gpu.fnk or the base_normalizer: facenorm/crop2x.v2_maxsize400.cpu.fnk, depending on your acceleration type:

GPU

objects:
  ...
  face:
    base_normalizer: facenorm/crop2x.v2_maxsize400.gpu.fnk
    quality_attribute: face_quality
  ...

CPU

objects:
  ...
  face:
    base_normalizer: facenorm/crop2x.v2_maxsize400.cpu.fnk
    quality_attribute: face_quality
  ...

Specify the face normalizer models in the normalizers section by pasting the following code:

GPU

normalizers:
  ...
  models:
    crop1x:
      model: facenorm/crop1x.v2_maxsize400.gpu.fnk
    crop2x:
      model: facenorm/crop2x.v2_maxsize400.gpu.fnk
    cropbbox:
      model: facenorm/cropbbox.v2.gpu.fnk
    multicrop_full_center:
      model: ''
    multicrop_full_crop2x:
      model: facenorm/facenorm.multicrop_full_crop2x_size400.gpu.fnk
    norm200:
      model: facenorm/bee.v3.gpu.fnk
  ...

CPU

normalizers:
  ...
  models:
    crop1x:
      model: facenorm/crop1x.v2_maxsize400.cpu.fnk
    crop2x:
      model: facenorm/crop2x.v2_maxsize400.cpu.fnk
    cropbbox:
      model: facenorm/cropbbox.v2.cpu.fnk
    multicrop_full_center:
      model: ''
    multicrop_full_crop2x:
      model: facenorm/facenorm.multicrop_full_crop2x_size400.cpu.fnk
    norm200:
      model: facenorm/bee.v3.cpu.fnk
  ...

Note

This step is required to enable face attribute recognition.

To enable face attribute recognition, do the following:

In the /opt/findface-multi/configs/findface-extraction-api/findface-extraction-api.yaml configuration file, specify the extraction models in the extractors section, as shown in the example below. Be sure to indicate the right acceleration type for each model, matching the acceleration type of findface-extraction-api: CPU or GPU.

GPU

extractors:
  ...
  models:
    face_age: faceattr/age.v2.gpu.fnk
    face_beard: faceattr/beard.v0.gpu.fnk
    face_beard4: ''
    face_countries47: ''
    face_emben: face/mango_320.gpu.fnk
    face_emotions: faceattr/emotions.v1.gpu.fnk
    face_eyes_attrs: ''
    face_eyes_openness: ''
    face_gender: faceattr/gender.v2.gpu.fnk
    face_glasses3: faceattr/glasses3.v0.gpu.fnk
    face_glasses4: ''
    face_hair: ''
    face_headpose: faceattr/headpose.v3.gpu.fnk
    face_headwear: ''
    face_highlight: ''
    face_liveness: faceattr/liveness.web.v0.gpu.fnk
    face_luminance_overexposure: ''
    face_luminance_underexposure: ''
    face_luminance_uniformity: ''
    face_medmask3: faceattr/medmask3.v2.gpu.fnk
    face_medmask4: ''
    face_mouth_attrs: ''
    face_quality: faceattr/quality_fast.v1.gpu.fnk
    face_scar: ''
    face_sharpness: ''
    face_tattoo: ''
    face_validity: ''

CPU

extractors:
  ...
  models:
    face_age: faceattr/age.v2.cpu.fnk
    face_beard: faceattr/beard.v0.cpu.fnk
    face_beard4: ''
    face_countries47: ''
    face_emben: face/mango_320.cpu.fnk
    face_emotions: faceattr/emotions.v1.cpu.fnk
    face_eyes_attrs: ''
    face_eyes_openness: ''
    face_gender: faceattr/gender.v2.cpu.fnk
    face_glasses3: faceattr/glasses3.v0.cpu.fnk
    face_glasses4: ''
    face_hair: ''
    face_headpose: faceattr/headpose.v3.cpu.fnk
    face_headwear: ''
    face_highlight: ''
    face_liveness: faceattr/liveness.web.v0.cpu.fnk
    face_luminance_overexposure: ''
    face_luminance_underexposure: ''
    face_luminance_uniformity: ''
    face_medmask3: faceattr/medmask3.v2.cpu.fnk
    face_medmask4: ''
    face_mouth_attrs: ''
    face_quality: faceattr/quality_fast.v1.cpu.fnk
    face_scar: ''
    face_sharpness: ''
    face_tattoo: ''
    face_validity: ''

The following extraction models are available:

Extractor	Acceleration	Configure as follows
age	CPU	`face_age: faceattr/age.v2.cpu.fnk`
age	GPU	`face_age: faceattr/age.v2.gpu.fnk`
beard	CPU	`face_beard: faceattr/beard.v0.cpu.fnk`
beard	GPU	`face_beard: faceattr/beard.v0.gpu.fnk`
individual face feature vector	CPU	`face_emben: face/mango_320.cpu.fnk`
individual face feature vector	GPU	`face_emben: face/mango_320.gpu.fnk`
gender	CPU	`face_gender: faceattr/gender.v2.cpu.fnk`
gender	GPU	`face_gender: faceattr/gender.v2.gpu.fnk`
emotions	CPU	`face_emotions: faceattr/emotions.v1.cpu.fnk`
emotions	GPU	`face_emotions: faceattr/emotions.v1.gpu.fnk`
glasses	CPU	`face_glasses3: faceattr/glasses3.v0.cpu.fnk`
glasses	GPU	`face_glasses3: faceattr/glasses3.v0.gpu.fnk`
head position	CPU	`face_headpose: faceattr/headpose.v3.cpu.fnk`
head position	GPU	`face_headpose: faceattr/headpose.v3.gpu.fnk`
face liveness	CPU	`face_liveness: faceattr/liveness.web.v0.cpu.fnk`
face liveness	GPU	`face_liveness: faceattr/liveness.web.v0.gpu.fnk`
face mask	CPU	`face_medmask3: faceattr/medmask3.v2.cpu.fnk`
face mask	GPU	`face_medmask3: faceattr/medmask3.v2.gpu.fnk`
face quality	CPU	`face_quality: faceattr/quality_fast.v1.cpu.fnk`
face quality	GPU	`face_quality: faceattr/quality_fast.v1.gpu.fnk`

Tip

To leave a model disabled, pass the empty value '' to the relevant parameter. Do not remove the parameter itself. Otherwise, the system will be searching for the default model.

extractors:
  face_age: ''
  face_beard: ''
  face_beard4: ''
  face_countries47: ''
  face_emben: ''
  face_emotions: ''
  face_eyes_attrs: ''
  face_eyes_openness: ''
  face_gender: ''
  face_glasses3: ''
  face_glasses4: ''
  face_hair: ''
  face_headpose: ''
  face_headwear: ''
  face_highlight: ''
  face_liveness: ''
  face_luminance_overexposure: ''
  face_luminance_underexposure: ''
  face_luminance_uniformity: ''
  face_medmask3: ''
  face_medmask4: ''
  face_mouth_attrs: ''
  face_quality: ''
  face_scar: ''
  face_sharpness: ''
  face_tattoo: ''
  face_validity: ''

Important

The face_liveness extraction model liveness.web.v0 is enabled by default. Do not disable it if you use authentication by face.

Restart the findface-multi-findface-extraction-api-1 container.

sudo docker container restart findface-multi-findface-extraction-api-1

To enable face recognition, modify the /opt/findface-multi/configs/findface-video-worker/findface-video-worker.yaml configuration file.

In the models section, specify the face neural network models by analogy with the example below:

GPU

sudo vi /opt/findface-multi/configs/findface-video-worker/findface-video-worker.yaml

models:
  ...
  detectors:
    ...
    face:
      fnk_path: /usr/share/findface-data/models/detector/face.jasmine_fast.003.gpu.fnk
      min_size: 60
    ...
  normalizers:
    ...
    face_norm:
      fnk_path: /usr/share/findface-data/models/facenorm/crop2x.v2_maxsize400.gpu.fnk
    face_norm_quality:
      fnk_path: /usr/share/findface-data/models/facenorm/crop1x.v2_maxsize400.gpu.fnk
    ...
  extractors:
    ...
    face_quality:
      fnk_path: /usr/share/findface-data/models/faceattr/quality_fast.v1.gpu.fnk
      normalizer: face_norm_quality

CPU

sudo vi /opt/findface-multi/configs/findface-video-worker/findface-video-worker.yaml

models:
  ...
  detectors:
    ...
    face:
      fnk_path: /usr/share/findface-data/models/detector/face.jasmine_fast.003.cpu.fnk
      min_size: 60
    ...
  normalizers:
    ...
    face_norm:
      fnk_path: /usr/share/findface-data/models/facenorm/crop2x.v2_maxsize400.cpu.fnk
    face_norm_quality:
      fnk_path: /usr/share/findface-data/models/facenorm/crop1x.v2_maxsize400.cpu.fnk
    ...
  extractors:
    ...
    face_quality:
      fnk_path: /usr/share/findface-data/models/faceattr/quality_fast.v1.cpu.fnk
      normalizer: face_norm_quality

Make sure that the objects -> face section is included:

objects:
  ...
  face:
    normalizer: face_norm
    quality: face_quality
    track_features: ''

Restart the findface-multi-findface-video-worker-1 container.

sudo docker container restart findface-multi-findface-video-worker-1

To enable face recognition, open the /opt/findface-multi/configs/findface-video-manager/findface-video-manager.yaml configuration file and make sure it contains the face section in detectors that looks similar to the example below.

sudo vi /opt/findface-multi/configs/findface-video-manager/findface-video-manager.yaml

detectors:
  ...
  face:
    filter_min_quality: 0.5
    filter_min_size: 60
    filter_max_size: 8192
    roi: ''
    fullframe_crop_rot: false
    fullframe_use_png: false
    jpeg_quality: 95
    overall_only: true
    realtime_post_first_immediately: false
    realtime_post_interval: 1
    realtime_post_every_interval: false
    track_interpolate_bboxes: true
    track_miss_interval: 1
    track_overlap_threshold: 0.25
    track_max_duration_frames: 0
    track_send_history: false
    post_best_track_frame: true
    post_best_track_normalize: true
    post_first_track_frame: false
    post_last_track_frame: false
    tracker_type: simple_iou
    track_deep_sort_matching_threshold: 0.65
    track_deep_sort_filter_unconfirmed_tracks: true
    track_object_is_principal: false
    track_history_active_track_miss_interval: 0

Note

This step is required to enable face attribute recognition.

Enable recognition of face attributes in the /opt/findface-multi/configs/findface-multi-legacy/findface-multi-legacy.py configuration file.
1. In the FFSECURITY section, specify the face attributes that you want to display for the face recognition events.
```
# available features: age, beard, emotions, gender, glasses, headpose, medmask
'FACE_EVENTS_FEATURES': ['glasses', 'beard', 'age', 'gender', 'headpose', 'medmask', 'emotions'],
```
2. Restart the findface-multi-findface-multi-legacy-1 container.
```
sudo docker container restart findface-multi-findface-multi-legacy-1
```