class ThreadedDetector: def __init__(self, cascade, size): self.past = [] self.haar = HaarDetector(cascade, size) self.haarResult = None self.thread = None def detect(self, image): res = None if len(self.past) == 0: res = self.haar.detect(image) else: if self.thread == None or self.thread.is_alive()==False: if self.haarResult != None: res = self.haarResult self.haarResult = None self.image = cv.CloneImage(image) self.thread = threading.Thread(target=ThreadedDetector.doThreadedHaar, args=(self, image)) self.thread.daemon = True self.thread.start() if res == None: res = self.past[len(self.past)-1] self.past.append(res) return res def doThreadedHaar(self, image): self.haarResult = self.haar.detect(self.image) #return self.haarResult
import cv2
import HaarDetector as Detector
from Recognizer import searchFace, drawRectangle, FrameCharacter
if __name__ == "__main__":
cap = cv2.VideoCapture("11.mp4")
cv2.namedWindow("Faces found", cv2.WINDOW_NORMAL)
font = cv2.FONT_HERSHEY_SIMPLEX
detector = Detector.HaarDetector()
while (1):
#Получаем кадр
ret, frame = cap.read()
#Характеристики кадра
FC = FrameCharacter(frame)
frameCharacter = FC.character()
#Область определения лица
cv2.rectangle(frame,
(int(frameCharacter["X0"]), int(frameCharacter["Y0"])),
(int(frameCharacter["X1"]), int(frameCharacter["Y1"])),
(255, 0, 0), 2)
faces = detector.detect(frame)
drawRectangle(frame, faces)
if (searchFace(frameCharacter, faces) == True):
cv2.putText(frame, "STOP ROTATING", (250, 250), font, 0.5,
(0, 0, 255), 2, cv2.LINE_AA)
else:
text = "Face not found."
def __init__(self, cascade, size): self.past = [] self.haar = HaarDetector(cascade, size) self.haarResult = None self.thread = None
