From 4e4553d5e95e034bc19b41dc7db9729326f8e392 Mon Sep 17 00:00:00 2001 From: "Xie, Zhengtian" Date: Thu, 14 Jan 2021 14:58:31 +0800 Subject: [PATCH] Show chinese name with OT --- face_reco_from_camera_ot_single_person.py | 38 +++++++++++++++-------- 1 file changed, 25 insertions(+), 13 deletions(-) diff --git a/face_reco_from_camera_ot_single_person.py b/face_reco_from_camera_ot_single_person.py index 4a6aaa3..d6bece1 100644 --- a/face_reco_from_camera_ot_single_person.py +++ b/face_reco_from_camera_ot_single_person.py @@ -14,11 +14,12 @@ import cv2 import os import pandas as pd import time +from PIL import Image, ImageDraw, ImageFont # Dlib 正向人脸检测器 (Use frontal face detector of Dlib) detector = dlib.get_frontal_face_detector() -# Dlib 人脸 landmark 特征点检测器 (Get face landmarks) +# Dlib 人脸 landmark 特征点检测器 (Use face landmarks predictor of Dlib) predictor = dlib.shape_predictor('data/data_dlib/shape_predictor_68_face_landmarks.dat') # Dlib Resnet 人脸识别模型，提取 128D 的特征矢量 (Use Dlib resnet50 model to get 128D face descriptor) @@ -91,16 +92,14 @@ class Face_Recognizer: print('##### End Warning #####') return 0 - # 计算两个128D向量间的欧式距离 (Compute the e-distance between two 128D features) - - # 更新 FPS (Update FPS of Video stream + # 更新 FPS (Update FPS of video stream) 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 - # 计算两个128D向量间的欧式距离 (Compute the e-distance between two 128D features) + # 计算两个128D向量间的欧式距离 (Compute the e-distance between two 128D features) @staticmethod def return_euclidean_distance(feature_1, feature_2): feature_1 = np.array(feature_1) @@ -116,6 +115,20 @@ class Face_Recognizer: cv2.LINE_AA) cv2.putText(img_rd, "Q: Quit", (20, 450), self.font, 0.8, (255, 255, 255), 1, cv2.LINE_AA) + def draw_name(self, img_rd): + # 在人脸框下面写人脸名字 / Write names under ROI + font = ImageFont.truetype("simsun.ttc", 30) + img = Image.fromarray(cv2.cvtColor(img_rd, cv2.COLOR_BGR2RGB)) + draw = ImageDraw.Draw(img) + draw.text(xy=self.current_frame_face_position_list[0], text=self.current_frame_name_list[0], font=font) + img_rd = cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR) + return img_rd + + def show_chinese_name(self): + # Default known name: person_1, person_2, person_3 + if self.current_frame_face_cnt >= 1: + self.name_known_list[0] ='张三'.encode('utf-8').decode() + # 处理获取的视频流，进行人脸识别 (Face detection and recognition wit OT from input video stream) def process(self, stream): # 1. 读取存放所有人脸特征的 csv (Get faces known from "features.all.csv") @@ -135,7 +148,7 @@ class Face_Recognizer: # 4.1 当前帧和上一帧相比没有发生人脸数变化 (If cnt not changes, 1->1 or 0->0) if self.current_frame_face_cnt == self.last_frame_faces_cnt: - print(" >>> scene 1: 当前帧和上一帧相比没有发生人脸数变化 (No face cnt changes in this frame!!!") + print(" >>> scene 1: 当前帧和上一帧相比没有发生人脸数变化 (No face cnt changes in this frame!!!)") if "unknown" in self.current_frame_name_list: print(" >>> 有未知人脸, 开始进行 reclassify_interval_cnt 计数") self.reclassify_interval_cnt += 1 @@ -208,15 +221,14 @@ class Face_Recognizer: self.current_frame_face_position_list[k] = tuple( [faces[k].left(), int(faces[k].bottom() + (faces[k].bottom() - faces[k].top()) / 4)]) - print(" >>> self.current_frame_name_list[k]: ", + print(" >>> self.current_frame_name_list: ", self.current_frame_name_list[k]) - print(" >>> self.current_frame_face_position_list[k]: ", + print(" >>> self.current_frame_face_position_list: ", self.current_frame_face_position_list[k]) - # 写名字 (Write names under ROI - img_rd = cv2.putText(img_rd, self.current_frame_name_list[k], - self.current_frame_face_position_list[k], self.font, 0.8, (0, 255, 255), 1, - cv2.LINE_AA) + # 在这里更改显示的人名 (Modify name if needed) + self.show_chinese_name() + img_rd = self.draw_name(img_rd) # 4.2 当前帧和上一帧相比发生人脸数变化 (If face cnt changes, 1->0 or 0->1) else: @@ -226,7 +238,7 @@ class Face_Recognizer: self.current_frame_face_feature_list = [] # 4.2.1 人脸数从 0->1 / Face cnt 0->1 - if (self.current_frame_face_cnt == 1): + if self.current_frame_face_cnt == 1: print(" >>> scene 2.1 出现人脸，进行人脸识别 (Get person in this frame and do face recognition)") self.current_frame_name_list = []