README

A face interface class implementing different face detection, alignment and recognition algorithms.

Algorithms Implemented

• Face Detector (detector_method='dlib')
• Dlib CNN Face Detector (detector_method='cnn')
• OpenCV Face Detector (detector_method='opencv')
• Mobilenet Face Detector (detector_method='mobilenet')
• Dlib Face Recognition (recognition_method='dlib')
• Dlib Facial Landmarks (predictor_model='small' for 5 face landmarks)
• server based detector- (detector_method='server') mobilenetSSD implementation
• server based recognizer - (recognition_method='server') insightFace+facenet implementation

Requirements

• dlib
• opencv
• numpy
• cudnn (for gpu supoort for cnn methods)

Installation

sudo apt-get install libboost-all-dev libopenblas-dev liblapacke-dev cmake build-essential
sudo apt-get install python-dev python-pip python-setuptools #python-opencv

pip install --user git+<https-url>

or

pip install --user git+ssh://[email protected]/macherlabs/facelib.git

How to use

import face, cv2
facedemo = face.Face(detector_method='dlib')
image_url1 = 'test.png'
image_url2 = 'test2.png'

imgcv1 = cv2.imread(image_url1)
imgcv2 = cv2.imread(image_url2)

if imgcv1 is not None and imgcv2 is not None:
    results = facedemo.compare(imgcv1, imgcv2)
    print results# facelib

Mobilenet usage

faceDetector = Face(detector_method='mobilenet',
         detector_model='mobilenet_300_frozen_trt_inference_graph_face.pb', # Default mobilenet_512_frozen_inference_graph_face.pb
         recognition_method=None ,
         gpu_frac=0.3,
         trt_enable=False,# converts graph to tensorrt optimized graph
         precision='FP16' # Defalut 'FP32', use 'FP16' only if gpu support is available
         )

Server based detector, recognizer usage

recog_config={"endpoint":"http://localhost",
        "apiPort":9000,
        "mlPort":6500,
        "api_version":"api/v1",
        "service":"recognition",
        "api_key":"00000000-0000-0000-0000-000000000002",
        "maxFailedAttempts":5000,
        "matchThreshold":0.6
        }
        
 detector_config ={
        "endpoint":"http://localhost",
        "port":9000,
        "route":"detect"
        }

faceDetector = Face(detector_method='mobilenet',
         detector_model='mobilenet_300_frozen_trt_inference_graph_face.pb', # Default mobilenet_512_frozen_inference_graph_face.pb
         recognition_method=None ,
         gpu_frac=0.3,
         trt_enable=False,# converts graph to tensorrt optimized graph
         precision='FP16' # Defalut 'FP32', use 'FP16' only if gpu support is available,
         det_server_config=detector_config,
         recog_server_config=recog_config
         )