231 lines
9.4 KiB
Python
231 lines
9.4 KiB
Python
# 进行人脸录入 / face register
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# 录入多张人脸 / support multi-faces
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import datetime
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import dlib
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import numpy as np
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import cv2
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import os
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import shutil # 读写文件
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import time
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import win32com.client
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from PIL import ImageDraw, ImageFont
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from PIL import Image
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action_list = ['look_ahead', 'look_left', 'look_right', 'rise_head', 'bow_head', 'blink', 'open_mouth', 'smile', 'over']
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action_map = {'look_ahead': '请看前方', 'blink': '请眨眼', 'open_mouth': '请张嘴',
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'smile': '请笑一笑', 'rise_head': '请抬头',
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'bow_head': '请低头', 'look_left': '请看左边',
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'look_right': '请看右边', 'over': '录入完成'}
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people_type_dict = {'0': 'elder', '1': 'worker', '2': 'volunteer'}
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# Dlib 正向人脸检测器
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# detector = dlib.get_frontal_face_detector()
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# OpenCV DNN face detector
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detector = cv2.dnn.readNetFromCaffe("data/data_opencv/deploy.prototxt.txt",
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"data/data_opencv/res10_300x300_ssd_iter_140000.caffemodel")
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class Face_Register:
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def __init__(self, people_type, id):
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self.init = False
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self.path_photos_from_camera = "data/data_faces_from_camera/"
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self.font = cv2.FONT_ITALIC
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self.existing_faces_cnt = 0 # 已录入的人脸计数器
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self.ss_cnt = 0 # 录入 personX 人脸时图片计数器
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self.faces_cnt = 0 # 录入人脸计数器
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# 之后用来控制是否保存图像的 flag
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self.save_flag = 1
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# 之后用来检查是否先按 'n' 再按 's'，即先新建文件夹再保存
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self.press_n_flag = 0
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# 之后用来提示动作的计数器
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self.index = 0
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self.frame_time = 0
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self.frame_start_time = 0
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self.fps = 0
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self.people_type = people_type_dict[str(people_type)]
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self.id = id
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def speak(self):
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text = action_map[action_list[self.index]]
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speak = win32com.client.Dispatch('Sapi.SpVoice')
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# speak.Voice = speak.GetVoices('Microsoft Zira')
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speak.Volume = 100
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speak.Rate = 2
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speak.Speak(text)
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# 新建保存人脸图像文件
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def pre_work_mkdir(self):
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if os.path.isdir(self.path_photos_from_camera):
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if os.path.isdir(self.path_photos_from_camera + '/' + self.people_type):
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pass
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else:
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os.mkdir(self.path_photos_from_camera + '/' + self.people_type)
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else:
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os.mkdir(self.path_photos_from_camera)
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# 删除之前存的人脸数据文件夹
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def pre_work_del_old_face_folders(self):
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# 删除之前存的人脸数据文件夹
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folders_rd = os.listdir(self.path_photos_from_camera)
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for i in range(len(folders_rd)):
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shutil.rmtree(self.path_photos_from_camera + folders_rd[i])
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if os.path.isfile("data/features_all.csv"):
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os.remove("data/features_all.csv")
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# 如果有之前录入的人脸, 在之前 person_x 的序号按照 person_x+1 开始录入 (v1)
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# 根据传入的人员类型和 id 录入 (v2)
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def check_existing_faces_cnt(self):
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if os.listdir("data/data_faces_from_camera/"):
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# 获取已录入的最后一个人脸序号
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person_list = os.listdir("data/data_faces_from_camera/")
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person_num_list = []
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for person in person_list:
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person_num_list.append(int(person.split('_')[-1]))
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self.existing_faces_cnt = max(person_num_list)
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# 如果第一次存储或者没有之前录入的人脸, 按照 1 开始录入
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# Start from 1
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else:
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self.existing_faces_cnt = 0
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# 获取处理之后 stream 的帧数
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def update_fps(self):
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now = time.time()
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self.frame_time = now - self.frame_start_time
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self.fps = 1.0 / self.frame_time
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self.frame_start_time = now
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# 生成的 cv2 window 上面添加说明文字
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def draw_note(self, img_rd):
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# 添加说明
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# cv2.putText(img_rd, action_map[action_list[index]].encode('utf-8').decode(), (20, 250), self.font, 1,
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# (0, 255, 0), 1, cv2.LINE_AA)
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cv2.putText(img_rd, "Face Register", (20, 40), self.font, 1, (255, 255, 255), 1, cv2.LINE_AA)
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cv2.putText(img_rd, "FPS: " + str(self.fps.__round__(2)), (20, 100), self.font, 0.8, (0, 255, 0), 1,
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cv2.LINE_AA)
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cv2.putText(img_rd, "Faces: " + str(self.faces_cnt), (20, 140), self.font, 0.8, (0, 255, 0), 1, cv2.LINE_AA)
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cv2.putText(img_rd, "N: Create face folder", (20, 350), self.font, 0.8, (255, 255, 255), 1, cv2.LINE_AA)
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cv2.putText(img_rd, "S: Save current face", (20, 400), self.font, 0.8, (255, 255, 255), 1, cv2.LINE_AA)
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cv2.putText(img_rd, "Q: Quit", (20, 450), self.font, 0.8, (255, 255, 255), 1, cv2.LINE_AA)
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font = ImageFont.truetype("simsun.ttc", 30, index=1)
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img_rd = Image.fromarray(cv2.cvtColor(img_rd, cv2.COLOR_BGR2RGB))
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draw = ImageDraw.Draw(img_rd)
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if self.index <= 7:
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draw.text((20, 230), text=action_map[action_list[self.index]].encode('utf-8').decode(), font=font,
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fill=(0, 255, 0))
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else:
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draw.text((20, 230), text=action_map[action_list[8]].encode('utf-8').decode(), font=font,
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fill=(0, 255, 0))
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img_rd = cv2.cvtColor(np.array(img_rd), cv2.COLOR_RGB2BGR)
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return img_rd
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# 获取人脸
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def process(self, img_rd):
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self.faces_cnt = 0
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(h, w) = img_rd.shape[:2]
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blob = cv2.dnn.blobFromImage(cv2.resize(img_rd, (300, 300)), 1.0,
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(300, 300), (104.0, 177.0, 123.0))
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detector.setInput(blob)
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faces = detector.forward()
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# # 新建存储人脸的文件夹
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# if self.index == 0:
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# # self.existing_faces_cnt += 1
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# current_face_dir = self.path_photos_from_camera + '/' + self.people_type + '/' + self.id
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# # current_face_dir = self.path_photos_from_camera + "person_" + str(self.existing_faces_cnt)
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# os.makedirs(current_face_dir)
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# # print('\n')
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# # print("新建的人脸文件夹 / Create folders: ", current_face_dir)
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#
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# self.ss_cnt = 0 # 将人脸计数器清零
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# self.index = 0
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# self.press_n_flag = 1 # 已经按下 'n'
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# 检测到人脸
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if faces.shape[2] != 0:
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# 矩形框
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for i in range(0, faces.shape[2]):
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# 计算矩形框大小
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confidence = faces[0, 0, i, 2]
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# filter out weak detections by ensuring the `confidence` is
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# greater than the minimum confidence
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if confidence < 0.5:
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continue
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self.faces_cnt += 1
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# compute the (x, y)-coordinates of the bounding box for the
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# object
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box = faces[0, 0, i, 3:7] * np.array([w, h, w, h])
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(startX, startY, endX, endY) = box.astype("int")
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height = (endY - startY)
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width = (endX - startX)
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# hh = int(height / 2)
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# ww = int(width / 2)
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# 判断人脸矩形框是否超出 480x640
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if endX > 640 or endY > 480 or startX < 0 or startY < 0:
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# if (endX + ww) > 640 or (endY + hh > 480) or (startX - ww < 0) or (
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# startY - hh < 0):
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cv2.putText(img_rd, "OUT OF RANGE", (20, 300), self.font, 0.8, (0, 0, 255), 1, cv2.LINE_AA)
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color_rectangle = (0, 0, 255)
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save_flag = 0
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print("请调整位置 / Please adjust your position")
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else:
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color_rectangle = (0, 255, 0)
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save_flag = 1
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cv2.rectangle(img_rd, tuple([startX, startY]), tuple([endX, endY]), color_rectangle, 2)
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# 根据人脸大小生成空的图像
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# img_blank = np.zeros((int(height * 2), width * 2, 3), np.uint8)
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img_blank = np.zeros((height, width, 3), np.uint8)
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# if save_flag:
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# # 保存摄像头中的人脸到本地
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# # 检查有没有先按'n'新建文件夹
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# if self.press_n_flag:
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# self.ss_cnt += 1
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#
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# if self.index <= 7:
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# for ii in range(height):
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# for jj in range(width):
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# img_blank[ii][jj] = img_rd[startY + ii][startX + jj]
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# cv2.imwrite(current_face_dir + "/img_face_" + str(self.ss_cnt) + ".jpg", img_blank)
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# print("写入本地 / Save into：",
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# str(current_face_dir) + "/img_face_" + str(self.ss_cnt) + ".jpg")
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# if self.index < len(action_list) - 1:
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# self.index += 1
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# self.speak()
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# else:
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# print("请先按 'N' 来建文件夹, 按 'S' / Please press 'N' and press 'S'")
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# # self.faces_cnt = len(faces)
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# 生成的窗口添加说明文字
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img_rd = self.draw_note(img_rd)
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self.update_fps()
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if not self.init:
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self.speak()
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self.init = True
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return img_rd
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def take_photo(self, frame):
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pass
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def run(self, frame):
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return self.process(frame)
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