利用opencv 做一个简单的人脸识别

文章目录

• 想开发一个属于自己的人脸识别系统， 动手开始吧

安装

• opencv 和 包模块opencv-contrib-python
• 安装失败的解决方案

pip uninstall opencv-python
pip uninstall opencv-contrib-python

pip install opencv-python
pip install opencv-contrib-python

• 完成后重启就可以了

实现

• 先对人脸进行识别
• 获取人脸特征图片并截取 灰度图保存
• 进行人脸模型训练
• 测试运行

人脸识别

• 运用了opencv 的人脸识别框架

face_cascade = cv.CascadeClassifier('haarcascade_frontalface_default.xml')

• 截取800 帧的人脸图片 并保存数据图片

face_cascade = cv.CascadeClassifier('haarcascade_frontalface_default.xml')
VIDEO_PATH ='video/hero2.mp4'
face_id =2#sampleNum用来计数样本数目
count =0
SAVE_PATH ='data/'

cap = cv.VideoCapture(VIDEO_PATH)
count =0while cap.isOpened():
    ret, img = cap.read()if ret isnotNone:if img isNone:continue
        img = imutils.resize(img, width=600)
        gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
        face = face_cascade.detectMultiScale(gray,1.3,5)for(x, y, w, h)in face:
            cv.rectangle(img,(x, y),(x + w, y + h),(255,0,0))
            count +=1ifnot os.path.exists(SAVE_PATH +'user.'+str(face_id)):
                os.mkdir(SAVE_PATH +'user.'+str(face_id))
            cv.imwrite(SAVE_PATH +'user.'+str(face_id)+"/count_"+str(count)+".jpg", gray[y: y + h, x: x + w])if count >=800:break   
        cv.imshow('h', img)
        key = cv.waitKey(1)if key ==27:breakelse:break
cap.release()
cv.destroyAllWindows()

测试用一个宝藏up主的人脸测试，打扰了，你要火

进行人脸模型训练

• 运用opencv 的face mok
• recog = cv.face.LBPHFaceRecognizer_create()

# 人脸识别器import time

recog = cv.face.LBPHFaceRecognizer_create()
recog.read('trainner/face.yaml')#创建一个函数，用于从数据集文件夹中获取训练图片,并获取id
time_start = time.process_time()defget_imgs_labels():
    face_id =0
    face_arr =[]
    face_ids =[]for user_id in os.listdir(SAVE_PATH):
        face_id = user_id.split('.')[1]
        user_path = SAVE_PATH + user_id
        image_paths =[os.path.join(user_path, key)for key in os.listdir(user_path)]for path in image_paths:
            face_ids.append(int(face_id))
            img = cv.imread(path,0)# img_arr = np.array(img, dtype="uint8")
            face_arr.append(img)return face_arr, face_ids

face_arr, face_ids = get_imgs_labels()
time_end = time.process_time ()print('runTime'+str((time_end - time_start)))
recog.train(train_img_gen)print('train'+str((time.process_time ()- time_end)))
recog.save('trainner/face.yaml')

• 训练完保存了一个模型文件
• 

识别人脸测试

• 先用人脸识别出人脸区域，截取出人脸区域，进行灰度化
• 输入到模型中预测
• 图片展示

VIDEO_PATH ='video/hero3.mp4'
font = cv.FONT_HERSHEY_SIMPLEX
idNum =0
names =['unknow','cc','dm']
cap = cv.VideoCapture(VIDEO_PATH)while cap.isOpened():
    ret, img = cap.read()
    img = imutils.resize(img, width=600)if ret isnotNone:
        gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
        face = face_cascade.detectMultiScale(gray,1.3,5)for(x, y, w, h)in face:
            cv.rectangle(img,(x, y),(x + w, y + h),(255,0,0))id, conf = recog.predict(gray[y: y+h, x: x+w])
            user =''if conf <100:
                user = names[id]
                conf ="{0}%".format(round(100-conf))else:
                user ="unknown"
                conf ="{0}%".format(round(100-conf))
            cv.putText(img, user,(x +5, y -5), font,1,(0,255,0),1)
            cv.putText(img,str(conf),(x +50, y -5), font,1,(0,255,0),1)
        cv.imshow('face', img)
        key = cv.waitKey(1)if key ==27:break
cap.release()
cv.destroyAllWindows()

效果展示

• 下面这个是训练的视频，上面是测试的视频

完整代码

# %%import cv2 as cv 
import numpy as np
import imutils
import os
from PIL import Image

# %%
face_cascade = cv.CascadeClassifier('haarcascade_frontalface_default.xml')
VIDEO_PATH ='video/hero2.mp4'
face_id =2#sampleNum用来计数样本数目
count =0
SAVE_PATH ='data/'

cap = cv.VideoCapture(VIDEO_PATH)
count =0while cap.isOpened():
    ret, img = cap.read()if ret isnotNone:if img isNone:continue
        img = imutils.resize(img, width=600)
        gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
        face = face_cascade.detectMultiScale(gray,1.3,5)for(x, y, w, h)in face:
            cv.rectangle(img,(x, y),(x + w, y + h),(255,0,0))
            count +=1ifnot os.path.exists(SAVE_PATH +'user.'+str(face_id)):
                os.mkdir(SAVE_PATH +'user.'+str(face_id))
            cv.imwrite(SAVE_PATH +'user.'+str(face_id)+"/count_"+str(count)+".jpg", gray[y: y + h, x: x + w])if count >=800:break   
        cv.imshow('h', img)
        key = cv.waitKey(1)if key ==27:breakelse:break
cap.release()
cv.destroyAllWindows()# %%import tensorflow.keras as keras
from keras.preprocessing.image import ImageDataGenerator

train_gen = ImageDataGenerator(rescale=1./255)
train_img_gen = train_gen.flow_from_directory('./data/')# %%# 人脸识别器import time

recog = cv.face.LBPHFaceRecognizer_create()
recog.read('trainner/face.yaml')#创建一个函数，用于从数据集文件夹中获取训练图片,并获取id
time_start = time.process_time()defget_imgs_labels():
    face_id =0
    face_arr =[]
    face_ids =[]for user_id in os.listdir(SAVE_PATH):
        face_id = user_id.split('.')[1]
        user_path = SAVE_PATH + user_id
        image_paths =[os.path.join(user_path, key)for key in os.listdir(user_path)]for path in image_paths:
            face_ids.append(int(face_id))
            img = cv.imread(path,0)# img_arr = np.array(img, dtype="uint8")
            face_arr.append(img)return face_arr, face_ids

face_arr, face_ids = get_imgs_labels()
time_end = time.process_time ()print('runTime'+str((time_end - time_start)))
recog.train(train_img_gen)print('train'+str((time.process_time ()- time_end)))
recog.save('trainner/face.yaml')# %%
VIDEO_PATH ='video/hero2.mp4'
font = cv.FONT_HERSHEY_SIMPLEX
idNum =0
names =['unknow','cc','dm']
cap = cv.VideoCapture(VIDEO_PATH)while cap.isOpened():
    ret, img = cap.read()
    img = imutils.resize(img, width=600)if ret isnotNone:
        gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
        face = face_cascade.detectMultiScale(gray,1.3,5)for(x, y, w, h)in face:
            cv.rectangle(img,(x, y),(x + w, y + h),(255,0,0))id, conf = recog.predict(gray[y: y+h, x: x+w])
            user =''if conf <100:
                user = names[id]
                conf ="{0}%".format(round(100-conf))else:
                user ="unknown"
                conf ="{0}%".format(round(100-conf))
            cv.putText(img, user,(x +5, y -5), font,1,(0,255,0),1)
            cv.putText(img,str(conf),(x +50, y -5), font,1,(0,255,0),1)
        cv.imshow('face', img)
        key = cv.waitKey(1)if key ==27:break
cap.release()
cv.destroyAllWindows()# %%