python检测人脸用的什么库_关于人脸检测python库的 初识 1

简介

上了一门计算机视觉的课程，初步了解， dlib python库

参考链接

原理

This face detector is made using the now classic Histogram of Oriented

Gradients (HOG) feature combined with a linear classifier, an image

pyramid, and sliding window detection scheme. This type of object detector

is fairly general and capable of detecting many types of semi-rigid objects

in addition to human faces. Therefore, if you are interested in making

your own object detectors then read the train_object_detector.py example program.

谷歌翻译

该面部检测器是使用现在经典的定向直方图(HOG)功能与线性分类器，图像金字塔和滑动窗口检测方案组合而成的。

这种类型的物体检测器相当通用，并且能够检测除人脸之外的许多类型的半刚性物体。

因此，如果您有兴趣制作自己的对象检测器，请阅读train_object_detector.py示例程序。

如果没有猜错应该使用了传统的方法？？

想得到分数

# Finally, if you really want to you can ask the detector to tell you the score

# for each detection. The score is bigger for more confident detections.

# The third argument to run is an optional adjustment to the detection threshold,

# where a negative value will return more detections and a positive value fewer.

# Also, the idx tells you which of the face sub-detectors matched. This can be

# used to broadly identify faces in different orientations.

code

# coding=utf-8

import dlib # 人脸算法库

from imageio import imread

import glob # 操作文件的相关模块

# 准备好人脸检测器和显示窗口，获取图片路径

detector = dlib.get_frontal_face_detector()

win = dlib.image_window()

paths=glob.glob('faces/*.jpg')

# 对每一张图片进行检测，并显示检测结果对应的矩形框

for path in paths:

img = imread(path)

# 1 表示将图片放大一杯，便于检测更过人脸

dets = detector(img, 1)

print('检测到了 %d 个人脸' % len(dets))

for i,d in enumerate(dets):

# 函数用于将一个可遍历的数据对象(如列表、元组或字符串)

# 组合为一个索引序列，同时列出数据和数据下标，一般用在 for 循环当中。

print("Detection {}: Left: {} Top: {} Right: {} Bottom: {}".format(i, d.left(), d.top(), d.right(), d.bottom())) # dets 是已经检测到的人脸

win.clear_overlay() # 清除覆盖

win.set_image(img)

win.add_overlay(dets)

dlib.hit_enter_to_continue()

dets, scores, idx = detector.run(img, 1, -1) # 其中1 表示放大 -1 表示 阈值 如果为正数那么相关的低于阈值的信息就会被筛选掉

for i, d in enumerate(dets):

print("Detection {}, score: {}, face_type:{}".format(d, scores[i], idx[i]))

结果

检测到了 1 个人脸

Detection 0: Left: 206 Top: 428 Right: 872 Bottom: 1094

Hit enter to continue

Detection [(206, 428) (872, 1094)], score: 2.9385107197297926, face_type:0

Detection [(114, 744) (176, 806)], score: -0.7111557926037881, face_type:2

Detection [(170, 847) (213, 890)], score: -0.8928528437771357, face_type:3

Detection [(121, 793) (196, 868)], score: -0.9795470083884772, face_type:1