engine.runAndWait()
flag=1
if not os.path.exists("Facedata"):
print("创建训练环境")
engine.say('正在创建训练环境')
os.mkdir("Facedata")
engine.say('创建成功')
engine.runAndWait()
flag=1
return flag
def getFace(cap,path_id):
# 调用笔记本内置摄像头，所以参数为0，如果有其他的摄像头可以调整参数为1，2
#cap = cv2.VideoCapture(0)
#xml文件为自己的文件路径
face_detector = cv2.CascadeClassifier(r'F:\npyWorkspace\venv\Lib\site-packages\cv2\data\haarcascade_frontalface_default.xml')
#face_id = input('\n enter user id:')
print('\n Initializing face capture. Look at the camera and wait ...')
count = 0
while True:
# 从摄像头读取图片
sucess, img = cap.read()
# 转为灰度图片
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# 检测人脸
faces = face_detector.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x+w, y+w), (255, 0, 0))
count += 1
# 保存图像
cv2.imwrite("Facedata/User." + str(path_id) + '.' + str(count) + '.jpg', gray[y: y + h, x: x + w])
cv2.imshow('image', img)
# 保持画面的持续。
k = cv2.waitKey(1)
if k == 27: # 通过esc键退出摄像
break
elif count >= 100: # 得到1000个样本后退出摄像
break
cv2.destroyAllWindows()
def getImagesAndLabels(path, detector):
imagePaths = [os.path.join(path, f) for f in os.listdir(path)] # join函数的作用
faceSamples = []
ids = []
for imagePath in imagePaths:
PIL_img = Image.open(imagePath).convert('L') # convert it to grayscale
img_numpy = np.array(PIL_img, 'uint8')
id = int(os.path.split(imagePath)[-1].split(".")[1])
faces = detector.detectMultiScale(img_numpy)
for (x, y, w, h) in faces:
faceSamples.append(img_numpy[y:y + h, x: x + w])
ids.append(id)
return faceSamples, ids
def trainFace():
# 人脸数据路径
path = 'Facedata'
recognizer = cv2.face.LBPHFaceRecognizer_create()
detector = cv2.CascadeClassifier(r'F:\npyWorkspace\venv\Lib\site-packages\cv2\data\haarcascade_frontalface_default.xml')
print('Training faces. It will take a few seconds. Wait ...')
faces, ids = getImagesAndLabels(path, detector)
recognizer.train(faces, np.array(ids))
recognizer.write(r'face_trainer\trainer.yml')
print("{0} faces trained. Exiting Program".format(len(np.unique(ids))))
def checkFace(cam,names,engine,sign_flag):
sex = {"female":"女士","male":"先生"}
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read('face_trainer/trainer.yml')
cascadePath = r"F:\npyWorkspace\venv\Lib\site-packages\cv2\data\haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascadePath)
font = cv2.FONT_HERSHEY_SIMPLEX
idnum = 0
names = ['yumengzhen', 'dujuanjuan','litingting','kangming','wangyizhe']
#cam = cv2.VideoCapture(0)
minW = 0.1 * cam.get(3)
minH = 0.1 * cam.get(4)
while True:
ret, img = cam.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
鹤望兰-02162024-06-12别下，是一个pdf，没有源码 #毫无价值 #标题与内容不符
