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get_faces_from_camera.py
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# 进行人脸录入 / face register
# 录入多张人脸 / support multi-faces
# Author: coneypo
# Blog: http://www.cnblogs.com/AdaminXie
# GitHub: https://github.com/coneypo/Dlib_face_recognition_from_camera
# Mail: [email protected]
# Created at 2018-05-11
# Updated at 2019-04-12
import dlib # 人脸处理的库 Dlib
import numpy as np # 数据处理的库 Numpy
import cv2 # 图像处理的库 OpenCv
import os # 读写文件
import shutil # 读写文件
# Dlib 正向人脸检测器 / frontal face detector
detector = dlib.get_frontal_face_detector()
# Dlib 68 点特征预测器 / 68 points features predictor
predictor = dlib.shape_predictor('data/data_dlib/shape_predictor_68_face_landmarks.dat')
# OpenCv 调用摄像头 use camera
cap = cv2.VideoCapture(0)
# 设置视频参数 set camera
cap.set(3, 480)
# 人脸截图的计数器 the counter for screen shoot
cnt_ss = 0
# 存储人脸的文件夹 the folder to save faces
current_face_dir = ""
# 保存 faces images 的路径 the directory to save images of faces
path_photos_from_camera = "data/data_faces_from_camera/"
# 新建保存人脸图像文件和数据CSV文件夹
# mkdir for saving photos and csv
def pre_work_mkdir():
# 新建文件夹 / make folders to save faces images and csv
if os.path.isdir(path_photos_from_camera):
pass
else:
os.mkdir(path_photos_from_camera)
pre_work_mkdir()
##### optional/可选, 默认关闭 #####
# 删除之前存的人脸数据文件夹
# delete the old data of faces
def pre_work_del_old_face_folders():
# 删除之前存的人脸数据文件夹
# 删除 "/data_faces_from_camera/person_x/"...
folders_rd = os.listdir(path_photos_from_camera)
for i in range(len(folders_rd)):
shutil.rmtree(path_photos_from_camera+folders_rd[i])
if os.path.isfile("data/features_all.csv"):
os.remove("data/features_all.csv")
# 这里在每次程序录入之前, 删掉之前存的人脸数据
# 如果这里打开，每次进行人脸录入的时候都会删掉之前的人脸图像文件夹 person_1/,person_2/,person_3/...
# If enable this function, it will delete all the old data in dir person_1/,person_2/,/person_3/...
# pre_work_del_old_face_folders()
##################################
# 如果有之前录入的人脸 / if the old folders exists
# 在之前 person_x 的序号按照 person_x+1 开始录入 / start from person_x+1
if os.listdir("data/data_faces_from_camera/"):
# 获取已录入的最后一个人脸序号 / get the num of latest person
person_list = os.listdir("data/data_faces_from_camera/")
person_num_list = []
for person in person_list:
person_num_list.append(int(person.split('_')[-1]))
person_cnt = max(person_num_list)
# 如果第一次存储或者没有之前录入的人脸, 按照 person_1 开始录入
# start from person_1
else:
person_cnt = 0
# 之后用来控制是否保存图像的 flag / the flag to control if save
save_flag = 1
# 之后用来检查是否先按 'n' 再按 's' / the flag to check if press 'n' before 's'
press_n_flag = 0
while cap.isOpened():
flag, img_rd = cap.read()
# print(img_rd.shape)
# It should be 480 height * 640 width
kk = cv2.waitKey(1)
img_gray = cv2.cvtColor(img_rd, cv2.COLOR_RGB2GRAY)
# 人脸数 faces
faces = detector(img_gray, 0)
# 待会要写的字体 / font to write
font = cv2.FONT_HERSHEY_COMPLEX
# 按下 'n' 新建存储人脸的文件夹 / press 'n' to create the folders for saving faces
if kk == ord('n'):
person_cnt += 1
current_face_dir = path_photos_from_camera + "person_" + str(person_cnt)
os.makedirs(current_face_dir)
print('\n')
print("新建的人脸文件夹 / Create folders: ", current_face_dir)
cnt_ss = 0 # 将人脸计数器清零 / clear the cnt of faces
press_n_flag = 1 # 已经按下 'n' / have pressed 'n'
# 检测到人脸 / if face detected
if len(faces) != 0:
# 矩形框 / show the rectangle box
for k, d in enumerate(faces):
# 计算矩形大小
# we need to compute the width and height of the box
# (x,y), (宽度width, 高度height)
pos_start = tuple([d.left(), d.top()])
pos_end = tuple([d.right(), d.bottom()])
# 计算矩形框大小 / compute the size of rectangle box
height = (d.bottom() - d.top())
width = (d.right() - d.left())
hh = int(height/2)
ww = int(width/2)
# 设置颜色 / the color of rectangle of faces detected
color_rectangle = (255, 255, 255)
# 判断人脸矩形框是否超出 480x640
if (d.right()+ww) > 640 or (d.bottom()+hh > 480) or (d.left()-ww < 0) or (d.top()-hh < 0):
cv2.putText(img_rd, "OUT OF RANGE", (20, 300), font, 0.8, (0, 0, 255), 1, cv2.LINE_AA)
color_rectangle = (0, 0, 255)
save_flag = 0
if kk == ord('s'):
print("请调整位置 / Please adjust your position")
else:
color_rectangle = (255, 255, 255)
save_flag = 1
cv2.rectangle(img_rd,
tuple([d.left() - ww, d.top() - hh]),
tuple([d.right() + ww, d.bottom() + hh]),
color_rectangle, 2)
# 根据人脸大小生成空的图像 / create blank image according to the size of face detected
im_blank = np.zeros((int(height*2), width*2, 3), np.uint8)
if save_flag:
# 按下 's' 保存摄像头中的人脸到本地 / press 's' to save faces into local images
if kk == ord('s'):
# 检查有没有先按'n'新建文件夹 / check if you have pressed 'n'
if press_n_flag:
cnt_ss += 1
for ii in range(height*2):
for jj in range(width*2):
im_blank[ii][jj] = img_rd[d.top()-hh + ii][d.left()-ww + jj]
cv2.imwrite(current_face_dir + "/img_face_" + str(cnt_ss) + ".jpg", im_blank)
print("写入本地 / Save into：", str(current_face_dir) + "/img_face_" + str(cnt_ss) + ".jpg")
else:
print("请在按 'S' 之前先按 'N' 来建文件夹 / Please press 'N' before 'S'")
# 显示人脸数 / show the numbers of faces detected
cv2.putText(img_rd, "Faces: " + str(len(faces)), (20, 100), font, 0.8, (0, 255, 0), 1, cv2.LINE_AA)
# 添加说明 / add some statements
cv2.putText(img_rd, "Face Register", (20, 40), font, 1, (0, 0, 0), 1, cv2.LINE_AA)
cv2.putText(img_rd, "N: New face folder", (20, 350), font, 0.8, (0, 0, 0), 1, cv2.LINE_AA)
cv2.putText(img_rd, "S: Save current face", (20, 400), font, 0.8, (0, 0, 0), 1, cv2.LINE_AA)
cv2.putText(img_rd, "Q: Quit", (20, 450), font, 0.8, (0, 0, 0), 1, cv2.LINE_AA)
# 按下 'q' 键退出 / press 'q' to exit
if kk == ord('q'):
break
# 如果需要摄像头窗口大小可调 / uncomment this line if you want the camera window is resizeable
# cv2.namedWindow("camera", 0)
cv2.imshow("camera", img_rd)
# 释放摄像头 / release camera
cap.release()
cv2.destroyAllWindows()