中科创达实训第十五天：人脸识别算法

一、课件

二、课后习题

三、答案

import cv2
import numpy as np
import sqlite3
import os
import face_recognition


# 1、从本地目录，打开一个人脸的图片，返回图片数据
def load_face_image_data(path):
    image_data = cv2.imread(path)
    return image_data


# 2、对人脸图片进行平移操作（向右移25像素，向上移15像素），返回新图片的数据
def move_face_image(image):
    img = cv2.imread(image)
    rows, cols = img.shape[:2]
    M = np.float32([[1, 0, 25], [0, 1, -15]])
    image_new_data = cv2.warpAffine(img, M, (cols, rows))
    return image_new_data


# 3、创建一个face.db数据库（SQLite3），新建face表
# 包含id，name，image_path三个字段
def sqlite_exec_sql(conn, sql):
    c = conn.cursor()
    c.execute(sql)
    conn.commit()
    print("Total number of rows changes :", conn.total_changes)


def sqlite_query(conn, sql):
    c = conn.cursor()
    cursor = c.execute(sql)
    return cursor


def creat_table():
    conn = sqlite3.connect('face.db')
    SQL_CREATE_TABLE = \
        '''
        CREATE TABLE FACE(
            ID             INTEGER  PRIMARY KEY  NOT NULL,
            NAME           TEXT      NOT NULL,
            IMAGE_PATH     CHAR(255) NOT NULL
        );'''
    # 新建表
    sqlite_exec_sql(conn, SQL_CREATE_TABLE)
    print("Table created successfully")
    conn.close()


# 4、实现人脸记录的插入、删除、查询功能（三个函数）
def insert_face_data(name, img_path):
    conn = sqlite3.connect('face.db')
    SQL_INSET_DATA = \
        "INSERT INTO FACE (NAME,IMAGE_PATH) VALUES ('" + name +"','"+ img_path + "')"
    # 插入数据
    print(SQL_INSET_DATA)
    sqlite_exec_sql(conn, SQL_INSET_DATA)
    conn.close()


def delete_face_data(id):
    conn = sqlite3.connect('face.db')
    SQL_DELETE_DATA = "DELETE from FACE where ID='"+str(id)+"';"
    # 插入数据
    sqlite_exec_sql(conn, SQL_DELETE_DATA)
    conn.close()


def query_face_data_all():
    conn = sqlite3.connect('face.db')
    SQL_QUERY_DATA_ALL = "SELECT * from FACE;"
    res = sqlite_query(conn, SQL_QUERY_DATA_ALL)
    temp = []
    for item in res:
        temp.append({'id':item[0] ,"data":{"name":item[1],'img_path':item[2]}})
    conn.close()
    return temp


def query_face_data_by_name(name):
    conn = sqlite3.connect('face.db')
    SQL_QUERY_DATA_ALL = "SELECT * from FACE where name = '"+ name +"';"
    res = sqlite_query(conn, SQL_QUERY_DATA_ALL)
    temp = []
    for item in res:
        temp.append({'id': item[0], "data": {"name": item[1], 'img_path': item[2]}})
    conn.close()
    return temp

# 5、扫描LFW数据集，把前面100个人脸的名字和图片(后缀为0001)的信息插入face表的功能
def insert_face_lfw(path):
    def traverse(path, pathsDic):
        tempFilePath = ''
        tempFileName = ''
        tempPerName = ''
        filePath = [os.path.join(path, f) for f in os.listdir(path)]
        for itemPath in filePath:
            if os.path.isdir(itemPath):
                traverse(itemPath, pathsDic)
            elif os.path.isfile(itemPath):
                if itemPath.split("\\")[-1].split(".")[0][-4:] == '0001':
                    tempFileName = itemPath.split("\\")[-1]
                    tempFilePath = itemPath.split("\\")[0] + "/" +itemPath.split("\\")[1]+"/" +itemPath.split("\\")[2]
                    tempPerName = itemPath.split("\\")[1]

            else:
                print("未知，出现错误")
        pathsDic.append({"path":tempFilePath, "imgName":tempFileName,"name":tempPerName})
        return tempFilePath, tempFileName, tempPerName
    result = []
    traverse(path, result)
    del result[-1]
    return result


# 6、实现人脸识别算法（打桩，返回值：人名，为指定值）
def face_test(paths, unknown):
    known_faces = []
    for item in paths:
        known_face = face_recognition.load_image_file(item['path'])
        known_face_encoding = face_recognition.face_encodings(known_face)[0]
        known_faces.append(known_face_encoding)

    unknown_image = face_recognition.load_image_file(unknown)
    try:
        unknown_face_encoding = face_recognition.face_encodings(unknown_image)[0]
    except IndexError:
        print("I wasn't able to locate any faces in at least one of the images. Check the image files. Aborting...")
        quit()

    results = face_recognition.compare_faces(known_faces, unknown_face_encoding)
    index = results.index(True)
    return paths[index]["name"]


# 7、实现人脸身份验证的功能，输入为人脸图片，调用人脸识别算法，从在根据人名从数据库中查询，看是否为合法用户
def face_database(name):
    res = query_face_data_by_name(name)
    # print(res)
    if res != []:
        print("合法用户")
    else:
        print("不合法用户")

if __name__ == "__main__":
    # 需要识别的人脸信息
    unknown = "faceimg/face.jpg" #Aaron_Eckhart_0001

    # 加载图片
    # res = load_face_image_data(unknown)
    # print(res)

    # 平移图片
    # res = move_face_image(unknown)
    # cv2.imshow("move",res)
    # cv2.waitKey(0)

    # 新建数据库
    # creat_table()

    # 删除数据通过id
    # delete_face_data(1)

    # 查询表中所有数据
    # data = query_face_data_all()
    # print(data)

    # 所有照片所在文件夹
    path = "faceimg/lfw"

    # 遍历照片插入数据库
    result = insert_face_lfw(path)
    # for item in result:
    #     insert_face_data(item["name"],item["path"])

    # 人脸识别，返回识别到的人名，
    print("识别中……")
    res = face_test(result, unknown)
    print(res, "名字")