Getting stated with the Python SDK

# copy wheel url from 
# https://github.com/getchui/offline_sdk/releases/latest
# and run
# pip install [wheel_url]

# for example for Linux:
pip install https://github.com/getchui/offline_sdk/releases/download/0.6.6/trueface-0.6.6-cp36-cp36m-linux_x86_64.whl

# for a Mac:
pip install https://github.com/getchui/offline_sdk/releases/download/0.6.6/trueface-0.6.6-cp36-cp36m-macosx_10_14_x86_64.whl


#install pip on Mac
sudo easy_install pip

collection
├── Manuel
│   ├── profile2015.png
│   └── profile.png
└── Nezare
    ├── 10.jpg
    └── 11.jpg

from trueface.recognition import FaceRecognizer
from trueface.video import VideoStream
import cv2


fr = FaceRecognizer(ctx='cpu',
                    fd_model_path='./fd_model',
                    fr_model_path='./model-tfv4/model.trueface',
                    params_path='./model-tfv4/model.params',
                    license='<your license key>'
                    )

fr.create_collection(folder='collection', name='collection.npz', return_features=False)

# src=0 is your usb device 0 which is the first connected usb camera
# if you are using an IP camera you would enter the URL here:
# example for an Amcrest IP camera: 
# src="rtsp://username:password@192.168.0.27:554/cam/realmonitor?channel=1&subtype=2"
vcap = VideoStream(src=0).start()

while(True):
    frame = vcap.read()
    frame = cv2.resize(frame, (640, 480))
    bounding_boxes, points, chips = fr.find_faces(frame,
                                              return_chips=True,
                                              return_binary=True)
    if bounding_boxes is None:
            continue
    for i, chip in enumerate(chips):
        identity = fr.identify(chip,
                               threshold=0.3,
                               collection='./collection.npz')
        print(identity)
        if 'predicted_label' in identity:
            fr.draw_label(
                frame,
                (int(bounding_boxes[i][0]),
                 int(bounding_boxes[i][1])),
                identity['predicted_label'])
        fr.draw_box(frame, bounding_boxes[i])
    cv2.imshow('Trueface.ai', frame)
    if cv2.waitKey(3

# hit "q" to quit the face recognition
python live_face_recognition.py