def run(in_='media/test_1.mp4', out='media/test_1_out.mp4'):
face_detector('dataset/live_stream_images')
liveStream('dataset/live_stream_images_out', in_, out)
from configs.app_face_detection_config import THRESHOLD, \
PRETRAINED_MODEL_RES10, PRETRAINED_MODEL_OPENCV, PRETRAINED_MODEL_RETAIL_0044
from configs.app_age_prediction_config import PRETRAINED_MODEL as PRETRAINED_MODEL_AGE
from face_detection import face_detector
from age_prediction import age_predictor
import cv2
if __name__ == "__main__":
output_path = "./output/out.jpg"
image = cv2.imread(filename="./img/amanda_bynes.jpg")
image_marked, face_bboxes, t_elapsed = face_detector(
image=image,
pretrained_model=PRETRAINED_MODEL_RETAIL_0044,
threshold=THRESHOLD,
output_path=output_path)
print("face bboxes: ", face_bboxes)
print("elapsed time: ", t_elapsed)
image_marked, ages, t_elapsed = age_predictor(
image=image_marked,
pretrained_model=PRETRAINED_MODEL_AGE,
bboxes=face_bboxes,
output_path=output_path)
print("ages: ", ages)
print("elapsed time: ", t_elapsed)
cv2.imshow("age", image_marked)
#USE GUI for running the specific case of searching from database.
#or Use each command line.
#for face detection stuff
from face_detection import face_detector
face_detector('dataset/Test_data_full')
#for example for matching faces
from face_match_v3 import match_faces
mn, tn, ml, aa = match_faces('dataset/missing_images_out',
'dataset/Test_data_full',
'matched/final_output_top3')
def run():
face_detector('dataset/live_stream_images')
liveStream('dataset/live_stream_images_out')
ap = argparse.ArgumentParser()
default_model = "../models/res10_300x300_ssd_iter_140000_fp16.caffemodel"
ap.add_argument("-p",
"--prototxt",
default="../models/deploy.prototxt",
help="path to facial landmark predictor")
ap.add_argument("-m",
"--model",
default=default_model,
help="path to facial landmark predictor")
ap.add_argument("-s",
"--shape-predictor",
default="../models/shape_predictor_68_face_landmarks.dat",
help="path to facial landmark predictor")
args = vars(ap.parse_args())
# initialize the detectors
detector = face_detection.face_detector(args["prototxt"], args["model"])
predictor = facial_landmark_detector(args["shape_predictor"])
cap = cv2.VideoCapture(0)
while cv2.waitKey(1) != 27:
ret, frame = cap.read()
(boxes, confidences) = detector.detect(frame)
shapes = predictor.predict(frame, boxes)
frame = detector.draw(frame, boxes, confidences)
frame = predictor.draw(frame, shapes)
cv2.imshow("Camera", frame)
def main(): face = face_detector() face.set_listener(f) face.detect()