from face_detection import FaceDetection
from face_recognition import FaceRecognition
from utils import read_image
if __name__ == "__main__":
# Init the Face Detection and Face Recognition classes
detection = FaceDetection()
recognition = FaceRecognition()
# Read the image
image = read_image('./yolov3/data/samples/person.jpg')
# Detect a face in the image (if many, returns the biggest one; if none, returns None)
bounding_box = detection.detect(image)
# bounding_box is a dictionary with parameters: x1, y1, x2, y2, width, height
print(bounding_box)
if bounding_box is not None:
# Plot the bounding box on the image
detection.plot(image, bounding_box)
# Extract the face from the image
face = recognition.extract(image, bounding_box)
# Check if the face is from an employee, return True or False
is_employee = recognition.recognize(face)
if is_employee:
print('Opening Door')
def main():
fd = FaceDetection()
fd.detect(MediaType.CAMERA)
#ラベルデータを取得するため、データセットをロード
with open(dir + pickle_file, mode='rb') as f:
image_data = pickle.load(f) #使わない
label_data = pickle.load(f) #使わない
index_to_label = pickle.load(f) #ラベル(数値）→ラベル(文字列)にするdict型データをロード
print('camera opend')
cv2.namedWindow("faces", cv2.WINDOW_AUTOSIZE) #顔画像表示用ウィンドウ
cv2.namedWindow("camera", cv2.WINDOW_NORMAL) #カメラ画像表示用ウィンドウ
key = 0
#mainループ
while (key != ord("q")): #'q'で停止
key = cv2.waitKey(50) #キー入力待ち(50msce)
img = cap.ReadCaputure() #カメラからframe画像を取得
draw_img = img.copy() #描画用の画像を取得
p_faces = detect.detect(draw_img) #顔の座標を取得
detect.draw_rec(draw_img, p_faces) #顔画像を赤線で描画
cv2.imshow("camera", draw_img) #画像表示
if (len(p_faces) != 0):
catface, images = detect.face_images(img, p_faces) #顔画像を取得
cv2.imshow("faces", catface)
if (key == ord("n")): #'n'押下で推論
for image in images:
gray_img = cv2.cvtColor(image,
cv2.COLOR_BGR2GRAY) #グレースケール画像に変換
predict = facerec.predict(gray_img) #推論
predict_label = index_to_label[predict[0]] #推論ラベルを取得
print("predict: " + predict_label)
#Create HeadPose model
headpose = HeadPose(ie, HEADPOSE_XML_PATH, HEADPOSE_BIN_PATH)
#init video from rtsp link
video = cv2.VideoCapture(CAM_ADDR)
#init video from build-in camera
# video = cv2.VideoCapture(0)
while (video.isOpened()):
ret, frame = video.read()
show_frame = frame.copy()
h, w, c = frame.shape
#get face on frame
outputs = facedetection.detect(frame)
if len(outputs) != 0:
outputs = np.array(outputs)
for output in outputs:
try:
#get face location
x_min, y_min, x_max, y_max = (output *
[w, h, w, h]).astype(int)
#crop face
img_cropped = frame[y_min:y_max, x_min:x_max]
#get face tilt
yaw = headpose.detect(img_cropped)['angle_y_fc'][0][0]
