Enable Face Attribute Recognition

Face attributes, such as age, gender, emotions, etc., are present in the filter set for detected face analysis during a case investigation.

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

Do the following:

1. Open the /opt/findface-cibr/configs/findface-extraction-api/findface-extraction-api.yaml configuration file.

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

2. Specify the relevant recognition 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. 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.

   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: ''
       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: ''
       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
   	GPU	face_age: faceattr/age.v2.gpu.fnk
   beard	CPU	face_beard: faceattr/beard.v0.cpu.fnk
   	GPU	face_beard: faceattr/beard.v0.gpu.fnk
   face feature vector	CPU	face_emben: face/mango_320.cpu.fnk
   	GPU	face_emben: face/mango_320.gpu.fnk
   gender	CPU	face_gender: faceattr/gender.v2.cpu.fnk
   	GPU	face_gender: faceattr/gender.v2.gpu.fnk
   emotions	CPU	face_emotions: faceattr/emotions.v1.cpu.fnk
   	GPU	face_emotions: faceattr/emotions.v1.gpu.fnk
   glasses	CPU	face_glasses3: faceattr/glasses3.v0.cpu.fnk
   	GPU	face_glasses3: faceattr/glasses3.v0.gpu.fnk
   face liveness	CPU	face_liveness: faceattr/liveness.web.v0.cpu.fnk
   	GPU	face_liveness: faceattr/liveness.web.v0.gpu.fnk
   face mask	CPU	face_medmask3: faceattr/medmask3.v2.cpu.fnk
   	GPU	face_medmask3: faceattr/medmask3.v2.gpu.fnk
   face quality	CPU	face_quality: faceattr/quality_fast.v1.cpu.fnk
   	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. E.g., to disable emotions and face mask recognition, pass the empty value to the corresponding extraction models:

   extractors:
     ...
     models:
       ...
       face_emotions: ''
       face_medmask3: ''
   

   Note

   You can find face attribute recognition models at /opt/findface-cibr/models/faceattr/.

   ls /opt/findface-cibr/models/faceattr/
   
   age.v2.cpu.fnk    emotions.v1.cpu.fnk  glasses3.v0.cpu.fnk      medmask3.v2.cpu.fnk
   age.v2.gpu.fnk    emotions.v1.gpu.fnk  glasses3.v0.gpu.fnk      medmask3.v2.gpu.fnk
   beard.v0.cpu.fnk  gender.v2.cpu.fnk    liveness.web.v0.cpu.fnk  quality_fast.v1.cpu.fnk
   beard.v0.gpu.fnk  gender.v2.gpu.fnk    liveness.web.v0.gpu.fnk  quality_fast.v1.gpu.fnk
   

3. Restart the findface-cibr-findface-extraction-api-1 container.

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

4. Enable recognition of face attributes in the /opt/findface-cibr/configs/findface-multi-legacy/findface-multi-legacy.py configuration file. In the FFSECURITY section, specify the face attributes that you want to display for the face recognition events.

   # make sure that corresponding extractors are licensed
   # and enabled at findface-extraction-api config file
   # available features: age, beard, emotions, gender, glasses, medmask
   'FACE_EVENTS_FEATURES': ['emotions', 'beard', 'gender', 'age', 'medmask', 'glasses'],
   

5. Restart the findface-cibr-findface-multi-legacy-1 container.

   sudo docker container restart findface-cibr-findface-multi-legacy-1