def main(args):
if sys.version_info < (3, 0):
print("Error: Python2 is slow. Use Python3 for max performance.")
return
cam_index = int(args.webcam)
resolutions = [
RESOLUTION_QVGA, RESOLUTION_VGA, RESOLUTION_HD, RESOLUTION_FULLHD
]
try:
cam_resolution = resolutions[int(args.resolution)]
except:
cam_resolution = RESOLUTION_QVGA
if args.detector:
try:
detector = FaceDetectorModels(int(args.detector))
print("Parameters: {}".format(detector))
process_facedetection(
detector,
FacePoseEstimatorModels.DEFAULT,
FaceAgeEstimatorModels.DEFAULT,
FaceGenderEstimatorModels.DEFAULT,
# FaceEmotionEstimatorModels.DEFAULT,
cam_resolution,
cam_index)
except:
print("Invalid parameter")
return
run(cam_index, cam_resolution)
def main(args):
if sys.version_info < (3, 0):
print("Error: Python2 is slow. Use Python3 for max performance.")
return
cam_index = int(args.webcam)
resolutions = [
RESOLUTION_QVGA, RESOLUTION_VGA, RESOLUTION_HD, RESOLUTION_FULLHD
]
try:
cam_resolution = resolutions[int(args.resolution)]
except:
cam_resolution = RESOLUTION_QVGA
if args.detector and args.encoder and args.liveness:
try:
detector = FaceDetectorModels(int(args.detector))
encoder = FaceEncoderModels(int(args.encoder))
liveness = FaceLivenessModels(int(args.liveness))
print("Parameters: {} {} {}".format(detector, encoder, liveness))
process_livenessdetection(detector, encoder, liveness, cam_index,
cam_resolution)
except:
print("Can not indentify your face, please try again!")
return
run(cam_index, cam_resolution)
def main(args):
if sys.version_info < (3, 0):
print("Error: Python2 is slow. Use Python3 for max performance.")
return
cam_index = int(args.webcam)
resolutions = [
RESOLUTION_QVGA, RESOLUTION_VGA, RESOLUTION_HD, RESOLUTION_FULLHD
]
try:
cam_resolution = resolutions[int(args.resolution)]
except:
cam_resolution = RESOLUTION_QVGA
if args.detector and args.encoder and args.speech_synthesizer:
try:
detector = FaceDetectorModels(int(args.detector))
encoder = FaceEncoderModels(int(args.encoder))
speech_synthesizer = SpeechSynthesizerModels(
int(args.speech_synthesizer))
print("Parameters: {} {} {}".format(detector, encoder,
speech_synthesizer))
process_facerecognition(detector, encoder, speech_synthesizer,
cam_index, cam_resolution)
except:
print("Invalid parameter")
return
run(cam_index, cam_resolution)
def main(args):
if sys.version_info < (3, 0):
print("Error: Python2 is slow. Use Python3 for max performance.")
return
cam_index = int(args.webcam)
resolutions = [
RESOLUTION_QVGA, RESOLUTION_VGA, RESOLUTION_HD, RESOLUTION_FULLHD
]
try:
cam_resolution = resolutions[int(args.resolution)]
except:
cam_resolution = RESOLUTION_VGA
if args.detector and args.name:
try:
detector = FaceDetectorModels(int(args.detector))
name = str(args.name)
print("Parameters: {}".format(detector))
process_faceenrollment(detector, cam_index, cam_resolution)
print("")
print("Processing of video recording started...")
#video_to_images(detector, "x" + INPUT_DIR_DATASET, name)
#video_to_images(detector, INPUT_DIR_DATASET, name, one_image_only=True)
video_to_images(detector, INPUT_DIR_DATASET, name)
print("Processing of video recording completed!")
print("Make sure to train the new datasets before testing!")
print("")
except:
print("Invalid parameter")
return
run(cam_index, cam_resolution, str(args.name))
def main(args):
if args.detector and args.encoder:
try:
detector = FaceDetectorModels(int(args.detector))
encoder = FaceEncoderModels(int(args.encoder))
classifier = FaceClassifierModels(int(args.classifier))
face_embeddings_path = args.face_embeddings_path
print("Parameters: {} {} {} {}".format(detector, encoder,
classifier,
face_embeddings_path))
train_recognition(detector, encoder, classifier,
face_embeddings_path, True)
print("\nImage dataset training completed!")
# generate audio samples for image datasets using text to speech synthesizer
if args.set_speech_synthesizer:
from libfaceid.speech_synthesizer import SpeechSynthesizerModels # lazy loading
speech_synthesizer = SpeechSynthesizerModels(
int(args.speech_synthesizer))
#print( "Parameters: {}".format(speech_synthesizer) )
train_audiosets(speech_synthesizer)
print("Audio samples created!")
except Exception as ex:
print(ex)
print("Invalid parameter")
return
run()
def main(args):
if sys.version_info < (3, 0):
print("Error: Python2 is slow. Use Python3 for max performance.")
return
redis_cam = RedisCam(**ConfigRedis.cam2)
resolutions = [ RESOLUTION_QVGA, RESOLUTION_VGA, RESOLUTION_HD, RESOLUTION_FULLHD ]
try:
cam_resolution = resolutions[int(args.resolution)]
except:
cam_resolution = RESOLUTION_QVGA
if args.detector is not None and args.encoder is not None:
try:
detector = FaceDetectorModels(int(args.detector))
encoder = FaceEncoderModels(int(args.encoder))
embeddings_path = args.embeddings_path
image_folder = args.image_folder
print( "Parameters: {} {}".format(detector, encoder) )
process_facerecognition(detector, encoder, redis_cam, cam_resolution, embeddings_path, image_folder)
except Exception as ex:
print( "Invalid parameter" )
print(ex)
return
def main(args):
if args.detector and args.encoder:
try:
detector = FaceDetectorModels(int(args.detector))
encoder = FaceEncoderModels(int(args.encoder))
classifier = FaceClassifierModels(int(args.classifier))
print("Parameters: {} {} {}".format(detector, encoder, classifier))
train_recognition(detector, encoder, classifier, True)
print("Training completed!")
except:
print("Invalid parameter")
return
run()
def main(args):
if sys.version_info < (3, 0):
print("Error: Python2 is slow. Use Python3 for max performance.")
return
if args.detector and args.encoder:
try:
detector = FaceDetectorModels(int(args.detector))
encoder = FaceEncoderModels(int(args.encoder))
print("Parameters: {} {}".format(detector, encoder))
process_facerecognition(detector, encoder, args.image)
except:
print("Invalid parameter")
return
run(args.image)
def init_model(int_detect=1, int_encode=3):
# Only for debugging while developing
try:
# Initialize face detection
global face_recognizer, face_detector, face_encoder
face_detector = FaceDetector(model=FaceDetectorModels(int_detect),
path=join(ROOT_DIR,
INPUT_DIR_MODEL_DETECTION))
# Initialize face recognizer
face_encoder = FaceEncoder(model=FaceEncoderModels(int_encode),
path=join(ROOT_DIR,
INPUT_DIR_MODEL_ENCODING),
path_training=join(
ROOT_DIR, INPUT_DIR_MODEL_TRAINING),
training=False)
face_recognizer = FaceRecognizer(face_embeddings_path=join(
ROOT_DIR, EMBEDDINGS_DIR + '/3_face_encodings_83.pickle'))
except Exception as ex:
face_encoder = None
print(ex)
def main(args):
if sys.version_info < (3, 0):
print("Error: Python2 is slow. Use Python3 for max performance.")
return
if args.detector and args.encoder:
try:
detector = FaceDetectorModels(int(args.detector))
encoder = FaceEncoderModels(int(args.encoder))
classifier = FaceEncoderModels(int(args.classifier))
print("Parameters: {} {} {}".format(detector, encoder, classifier))
train_recognition(detector, encoder, classifier, True)
fps = process_facerecognition(RESOLUTION_QVGA,
None,
0,
model_detector=detector,
model_recognizer=encoder)
print("Result: {}x{} {:.2f} fps".format(RESOLUTION_QVGA[0],
RESOLUTION_QVGA[1], fps))
except:
print("Invalid parameter")
return
run()