face_recognition 人脸识别模块

face_recognition 人脸识别模块

（安装之前，必须先安装dlib库）

1. 基于dlib库，进行了二次封装。号称是世界上最简洁的人脸识别库。

2. 训练数据集： 是麻省理工大学下属的学院 利用13000多张照片为基础。主要是以欧美人为主。

 在 command line下安装模块时：

F:\Python_AI\venv\Scripts> pip install face_recoginiton

 

• load_image_file : 加载要识别的人脸图像，返回Numpy数组，返回的是图片像素的特征向量（大小，方向）
• face_loctions: 定位图中人脸的坐标位置。返回矩形框的location（top,right,bottom,left）
• face_landmarks: 识别人脸的特征点; 返回68个特征点的坐标位置（chin....）
• face_encodings: 获取图像中所有人脸的编码信息（向量）
• compare_faces: 由面部编码信息进行面部识别匹配。

 

#!/usr/bin/env python
# !_*_ coding:utf-8 _*_

import face_recognition
from PIL import Image, ImageDraw
import cv2

# face_image = face_recognition.load_image_file('imgs/twis001.jpg')
face_image = cv2.imread('imgs/twis001.jpg')
face_marks_list = face_recognition.face_landmarks(face_image)

pil_image = Image.fromarray(face_image)
d = ImageDraw.Draw(pil_image)

for face_marks in face_marks_list:
    facial_features = [
        'chin',
        'left_eyebrow',
        'right_eyebrow',
        'nose_bridge',
        'nose_tip',
        'left_eye',
        'right_eye',
        'bottom_lip'
    ]
    for facial_feature in facial_features:
        # print("{}: 特征位置：{}".format(facial_feature, face_marks[facial_feature]))
        # d.line(face_marks[facial_feature], fill=(0, 255, 0), width=5)
        # d.point(face_marks[facial_feature], fill=(255, 0, 0))
        for p in face_marks[facial_feature]:
            print(p)
            cv2.circle(face_image, p, 1, (0, 255, 0), 1)

cv2.imshow("images", face_image)
cv2.imwrite("twis01.jpg",face_image)
cv2.waitKey(0)
cv2.destroyAllWindows()
# pil_image.show()

 

#!/usr/bin/env python
# !_*_ coding:utf-8 _*_

import face_recognition
from PIL import Image, ImageDraw, ImageFont

image_known = face_recognition.load_image_file('imgs/yangmi/yangmidanr00.jpg')
image_unknown = face_recognition.load_image_file('imgs/yangmi/yangmihe02.jpg')

image_known_encodings = face_recognition.face_encodings(image_known)[0]

face_locations = face_recognition.face_locations(image_unknown)

results = []

for i in range(len(face_locations)):
    top, right, bottom, left = face_locations[i]
    face_image = image_unknown[top:bottom, left:right]
    face_encoding = face_recognition.face_encodings(face_image)
    if face_encoding:
        result = {}
        matches = face_recognition.compare_faces(face_encoding, image_known_encodings, tolerance=0.5)
        if True in matches:
            print('在未知图片中找到了已知面孔')
            result['face_encoding'] = face_encoding
            result['is_view'] = True
            result['location'] = face_locations[i]
            result['face_id'] = i + 1
            results.append(result)

            if result['is_view']:
                print("已知面孔匹配照片上的第{}张脸！".format(result['face_id']))

pil_image = Image.fromarray(image_unknown)
draw = ImageDraw.Draw(pil_image)
view_face_locations = [i['location'] for i in results if i['is_view']]
for location in view_face_locations:
    top, right, bottom, left = location
    draw.rectangle([(left, top), (right, bottom)], outline=(0, 255, 0), width=2)
    font = ImageFont.truetype("consola.ttf", 20, encoding='unic')
    draw.text((left, top - 20), "yangmi", (255, 0, 0), font=font)

pil_image.show()

# 可以试着用cv2来画框，和写字 puttext

 

#!/usr/bin/env python
# !_*_ coding:utf-8 _*_

import face_recognition
import cv2

img_known = face_recognition.load_image_file("imgs/joedan/cows.jpeg")
img_unkown = face_recognition.load_image_file("imgs/joedan/joedan01.jpg")

face_encodings_known = face_recognition.face_encodings(img_known)
face_encodings_unknow = face_recognition.face_encodings(img_unkown)[0]
matches = face_recognition.compare_faces(face_encodings_known, face_encodings_unknow, tolerance=0.5)
print(matches)

locations = face_recognition.face_locations(img_known)
print(locations)
if True in matches:
    index = matches.index(True)
    match = locations[index]
    print(match)
    top, right, bottom, left = match
    cv2.rectangle(img_known, (left, top), (right, bottom), (0, 0, 255), 2)

cv2.imshow("images", img_known)
cv2.waitKey(0)
cv2.destroyAllWindows()