# 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: coneypo@foxmail.com # 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()