import cv2
face_cascade =
cv2.CascadeClassier(cv2.data.haarcascades+'haarcascade_frontalface_defau
lt.xml')
people_cascade =
cv2.CascadeClassier(cv2.data.haarcascades+'haarcascade_fullbody.xml')
eye_cascade =
cv2.CascadeClassier(cv2.data.haarcascades+'haarcascade_eye.xml')
# 调用摄像头摄像头
cap = cv2.VideoCapture("test.mp4")
var = "stand"
def create_neg_list():
with open('neg.txt', 'w') as f:
for img in os.listdir('data/myhaar/neg'):
line = 'neg/' + img + ''
f.write(line)
def detect_face(img):
face_cascade =
cv2.CascadeClassier('./cascades/haarcascades/haarcascade_frontalface_defa
ult.xml')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
def detect_eyes(img):
eye_cascade =
cv2.CascadeClassier('./cascades/haarcascades/haarcascade_eye.xml')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
eyes = eye_cascade.detectMultiScale(gray, 1.03, 5, 0, (40, 40))
for (x, y, w, h) in eyes:
img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 0, 255), 1)
def get_images_and_labels(path):
image_paths = [os.path.join(path,f) for f in os.listdir(path)]
#新建连个 list 用于存放
face_samples = []
ids = []
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