diff --git a/Class/collect_data/get_faces_from_camera.py b/Class/collect_data/get_faces_from_camera.py new file mode 100644 index 0000000..25240bf --- /dev/null +++ b/Class/collect_data/get_faces_from_camera.py @@ -0,0 +1,178 @@ +# 进行人脸录入 / face register +# 录入多张人脸 / support multi-faces + +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 +import time + +# Dlib 正向人脸检测器 +detector = dlib.get_frontal_face_detector() + + +class Face_Register: + def __init__(self): + self.path_photos_from_camera = "data/data_faces_from_camera/" + self.font = cv2.FONT_ITALIC + + self.existing_faces_cnt = 0 # 已录入的人脸计数器 + self.ss_cnt = 0 # 录入 personX 人脸时图片计数器 + self.faces_cnt = 0 # 录入人脸计数器 + + # 之后用来控制是否保存图像的 flag + self.save_flag = 1 + # 之后用来检查是否先按 'n' 再按 's'，即先新建文件夹再保存 + self.press_n_flag = 0 + + self.frame_time = 0 + self.frame_start_time = 0 + self.fps = 0 + + # 新建保存人脸图像文件 + def pre_work_mkdir(self): + if os.path.isdir(self.path_photos_from_camera): + pass + else: + os.mkdir(self.path_photos_from_camera) + + # 删除之前存的人脸数据文件夹 + def pre_work_del_old_face_folders(self): + # 删除之前存的人脸数据文件夹 + folders_rd = os.listdir(self.path_photos_from_camera) + for i in range(len(folders_rd)): + shutil.rmtree(self.path_photos_from_camera+folders_rd[i]) + if os.path.isfile("data/features_all.csv"): + os.remove("data/features_all.csv") + + # 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 + def check_existing_faces_cnt(self): + if os.listdir("data/data_faces_from_camera/"): + # 获取已录入的最后一个人脸序号 + 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])) + self.existing_faces_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: + self.existing_faces_cnt = 0 + + # 获取处理之后 stream 的帧数 + def update_fps(self): + now = time.time() + self.frame_time = now - self.frame_start_time + self.fps = 1.0 / self.frame_time + self.frame_start_time = now + + # 生成的 cv2 window 上面添加说明文字 + def draw_note(self, img_rd): + # 添加说明 + cv2.putText(img_rd, "Face Register", (20, 40), self.font, 1, (255, 255, 255), 1, cv2.LINE_AA) + cv2.putText(img_rd, "FPS: " + str(self.fps.__round__(2)), (20, 100), self.font, 0.8, (0, 255, 0), 1, + cv2.LINE_AA) + cv2.putText(img_rd, "Faces: " + str(self.faces_cnt), (20, 140), self.font, 0.8, (0, 255, 0), 1, cv2.LINE_AA) + cv2.putText(img_rd, "N: Create face folder", (20, 350), self.font, 0.8, (255, 255, 255), 1, cv2.LINE_AA) + cv2.putText(img_rd, "S: Save current face", (20, 400), self.font, 0.8, (255, 255, 255), 1, cv2.LINE_AA) + cv2.putText(img_rd, "Q: Quit", (20, 450), self.font, 0.8, (255, 255, 255), 1, cv2.LINE_AA) + + # 获取人脸 + def process(self, stream): + # 1. 新建储存人脸图像文件目录 + # self.pre_work_mkdir() + + # 2. 删除 "/data/data_faces_from_camera" 中已有人脸图像文件 + self.pre_work_del_old_face_folders() + + # 3. 检查 "/data/data_faces_from_camera" 中已有人脸文件 + self.check_existing_faces_cnt() + + while stream.isOpened(): + flag, img_rd = stream.read() # Get camera video stream + kk = cv2.waitKey(1) + faces = detector(img_rd, 0) # Use dlib face detector + + # 4. 按下 'n' 新建存储人脸的文件夹 + if kk == ord('n'): + self.existing_faces_cnt += 1 + current_face_dir = self.path_photos_from_camera + "person_" + str(self.existing_faces_cnt) + os.makedirs(current_face_dir) + print('\n') + print("新建的人脸文件夹 / Create folders: ", current_face_dir) + + self.ss_cnt = 0 # 将人脸计数器清零 + self.press_n_flag = 1 # 已经按下 'n' + + # 5. 检测到人脸 + if len(faces) != 0: + # 矩形框 + for k, d in enumerate(faces): + # 计算矩形框大小 + height = (d.bottom() - d.top()) + width = (d.right() - d.left()) + hh = int(height/2) + ww = int(width/2) + + # 6. 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), self.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) + + # 7. 根据人脸大小生成空的图像 + img_blank = np.zeros((int(height*2), width*2, 3), np.uint8) + + if save_flag: + # 8. 按下 's' 保存摄像头中的人脸到本地 + if kk == ord('s'): + # 检查有没有先按'n'新建文件夹 + if self.press_n_flag: + self.ss_cnt += 1 + for ii in range(height*2): + for jj in range(width*2): + img_blank[ii][jj] = img_rd[d.top()-hh + ii][d.left()-ww + jj] + cv2.imwrite(current_face_dir + "/img_face_" + str(self.ss_cnt) + ".jpg", img_blank) + print("写入本地 / Save into：", str(current_face_dir) + "/img_face_" + str(self.ss_cnt) + ".jpg") + else: + print("请先按 'N' 来建文件夹, 按 'S' / Please press 'N' and press 'S'") + self.faces_cnt = len(faces) + + # 9. 生成的窗口添加说明文字 + self.draw_note(img_rd) + + # 10. 按下 'q' 键退出 + if kk == ord('q'): + break + + self.update_fps() + cv2.namedWindow("camera", 1) + cv2.imshow("camera", img_rd) + + def run(self): + cap = cv2.VideoCapture(0) + self.process(cap) + + cap.release() + cv2.destroyAllWindows() + + +def main(): + Face_Register_con = Face_Register() + Face_Register_con.run() + + +if __name__ == '__main__': + main() \ No newline at end of file diff --git a/Class/live/RTMP_TRY.py b/Class/live/Live_BroadCast.py similarity index 91% rename from Class/live/RTMP_TRY.py rename to Class/live/Live_BroadCast.py index af6fb59..a726520 100644 --- a/Class/live/RTMP_TRY.py +++ b/Class/live/Live_BroadCast.py @@ -1,3 +1,5 @@ +# 进行摄像头直播推流 / live_broadcast + import cv2 as cv import time import subprocess as sp @@ -35,6 +37,7 @@ class stream_pusher(object): # 对获取的帧做一些画面处理的方法，返回完成处理的帧。 def __frame_handle__(self, raw_frame, text, shape1, shape2): # 帧用cv2进行一些处理，比如写上文本，画矩形等 + cv.putText(raw_frame, text.split('.')[0], (20, 40), cv.FONT_ITALIC, 0.8, (0, 0, 255), 1, cv.LINE_AA) return (raw_frame) # 向服务器推送 @@ -47,7 +50,7 @@ class stream_pusher(object): while True: # if not self.raw_frame_q.empty(): # 如果输入管道不为空 - # 把帧和相关信息从输入队列中取出 + # 把帧和相关信息从输入队列中取出 raw_frame, text, shape1, shape2 = self.raw_frame_q.get() # 对获取的帧进行画面处理 frame = self.__frame_handle__(raw_frame, text, shape1, shape2) @@ -85,14 +88,13 @@ if __name__ == '__main__': rtmpUrl = "rtmp://39.97.124.237:1984/wodelive" # 用vcl等直播软件播放时，也用这个地址 raw_q = multiprocessing.Queue() # 定义一个向推流对象传入帧及其他信息的队列 - time_q=multiprocessing.Queue() my_pusher = stream_pusher(rtmp_url=rtmpUrl, raw_frame_q=raw_q) # 实例化一个对象 my_pusher.run() # 让这个对象在后台推送视频流 while True: _, raw_frame = cap.read() - info = (raw_frame, '2', '3', '4') # 把需要送入队列的内容进行封装 + info = (raw_frame, str(datetime.datetime.now()), '3', '4') # 把需要送入队列的内容进行封装 # if not raw_q.full(): # 如果队列没满 raw_q.put(info) # 送入队列 cv.waitKey(1) diff --git a/Data/data_faces_from_camera/tmp.zip b/Data/data_faces_from_camera/tmp.zip new file mode 100644 index 0000000..15cb0ec Binary files /dev/null and b/Data/data_faces_from_camera/tmp.zip differ