Mo Meak 发布的帖子

# Face recognition with LBP descriptors.
# See Timo Ahonen's "Face Recognition with Local Binary Patterns".
#
# Before running the example:
# 1) Download the AT&T faces database http://www.cl.cam.ac.uk/Research/DTG/attarchive/pub/data/att_faces.zip
# 2) Exract and copy the orl_faces directory to the SD card root.
#AT&T faces库都是pgm后缀的图片，其他图片格式不支持，
#该AT&T faces库已经在文件夹里面，把该库解压并命名为att_faces，也可以是其他的命名，下面的路径要根据你的命名一样。
#待续
import sensor, time, image

SUB = "s1"
NUM_SUBJECTS = 5
NUM_SUBJECTS_IMGS = 10

#img = image.Image("/att_faces/%s/zhuren.pgm"%(SUB)).mask_ellipse()
img = image.Image("/att_faces/%s/1.pgm"%(SUB))# mask_ellipse()在API中并未找到，不用这个并不影响
d0 = img.find_lbp((0, 0, img.width(), img.height())) #从感兴趣的区域提取LBP（本地二进制模式）关键点
img = None #初始化

print("")
for s in range(1, NUM_SUBJECTS+1):
    dist = 0
    for i in range(2, NUM_SUBJECTS_IMGS+1):
#        img = image.Image("/att_faces/s%d/%d.pgm"%(s, i)).mask_ellipse()
        img = image.Image("/att_faces/s%d/%d.pgm"%(s, i))
        d1 = img.find_lbp((0, 0, img.width(), img.height()))
        dist += image.match_descriptor(d0, d1)
#对于LBP描述符，该函数返回一个表示整数的整数，两个描述符之间的差异。 然后你可以对此进行阈值/比较距离度量。
#距离是衡量相似度的指标。该越接近0，LBP关键点匹配越好。
    print("Average dist for subject %d: %d"%(s, dist/NUM_SUBJECTS_IMGS))

Open MV 例程里这个代码那一部分应该放对比的照片，那一部分放被对比的照片？求指教万分感谢

奥奥，是这样啊，那请问有没有摄像头识别人脸的源码

请在这里粘贴代码# Face recognition with LBP descriptors.
# See Timo Ahonen's "Face Recognition with Local Binary Patterns".
#
# Before running the example:
# 1) Download the AT&T faces database http://www.cl.cam.ac.uk/Research/DTG/attarchive/pub/data/att_faces.zip
# 2) Exract and copy the orl_faces directory to the SD card root.

import sensor, time, image

SUB = "s2"
NUM_SUBJECTS = 5
NUM_SUBJECTS_IMGS = 10

#img = image.Image("/att_faces/%s/xx.bmp"%(SUB)).mask_ellipse()
img = image.Image("/att_faces/%s/1.pgm"%(SUB))# mask_ellipse()在API中并未找到，不用这个并不影响
d0 = img.find_lbp((0, 0, img.width(), img.height())) #从感兴趣的区域提取LBP（本地二进制模式）关键点
img = None #初始化

print("")
for s in range(1, NUM_SUBJECTS+1):
    dist = 0
    for i in range(2, NUM_SUBJECTS_IMGS+1):
#        img = image.Image("/att_faces/s%d/xx.bmp"%(s, i)).mask_ellipse()
        img = image.Image("/att_faces/s%d/%d.pgm"%(s, i))
        d1 = img.find_lbp((0, 0, img.width(), img.height()))
        dist += image.match_descriptor(d0, d1)
#对于LBP描述符，该函数返回一个表示整数的整数，两个描述符之间的差异。 然后你可以对此进行阈值/比较距离度量。
#距离是衡量相似度的指标。该越接近0，LBP关键点匹配越好。
    print("Average dist for subject %d: %d"%(s, dist/NUM_SUBJECTS_IMGS))

为什么运行时摄像头闪一下白光，就没反应了？求指教

@kidswong999 在 人脸识别，求指教 中说：

orl_faces

是这个文件夹吗 ？

@kidswong999 import sensor, time, image

SUB = "s2"
NUM_SUBJECTS = 5
NUM_SUBJECTS_IMGS = 10

img = image.Image("orl_faces/%s/wx.jpg"%(SUB)).mask_ellipse()
d0 = img.find_lbp((0, 0, img.width(), img.height()))
img = None

print("")
for s in range(1, NUM_SUBJECTS+1):
dist = 0
for i in range(2, NUM_SUBJECTS_IMGS+1):
img = image.Image("orl_faces/s%d/%d.pgm"%(s, i)).mask_ellipse()
d1 = img.find_lbp((0, 0, img.width(), img.height()))
dist += image.match_descriptor(d0, d1)
print("Average dist for subject %d: %d"%(s, dist/NUM_SUBJECTS_IMGS))
这是完整的代码

@驻扎 请问下 你解决这个问题了吗

SUB = "s2"
NUM_SUBJECTS = 5
NUM_SUBJECTS_IMGS = 10

img = image.Image("I/wx.pgm"%(SUB)).mask_ellipse()
d0 = img.find_lbp((0, 0, img.width(), img.height()))
img = None

print("")
for s in range(1, NUM_SUBJECTS+1):
dist = 0
for i in range(2, NUM_SUBJECTS_IMGS+1):
img = image.Image("orl_faces/s%d/%d.pgm"%(s, i)).mask_ellipse()
d1 = img.find_lbp((0, 0, img.width(), img.height()))
dist += image.match_descriptor(d0, d1)
print("Average dist for subject %d: %d"%(s, dist/NUM_SUBJECTS_IMGS))

img = image.Image("I/wx.pgm"%(SUB)).mask_ellipse()
img = image.Image("orl_faces/s%d/%d.pgm"%(s, i)).mask_ellipse()
这两句代码我应该怎么改啊，老提示错误，求指教

@kidswong999 我把SD卡插在了MV上，img = image.Image("orl_faces/I/wx"%(SUB)).mask_ellipse()可是提示 这样的错误，那我应该怎么改呢？麻烦提示一下

import sensor, time, image
SUB = "s2"
NUM_SUBJECTS = 5
NUM_SUBJECTS_IMGS = 10

img = image.Image("orl_faces/%s/1.pgm"%(SUB)).mask_ellipse()
d0 = img.find_lbp((0, 0, img.width(), img.height()))
img = None

print("")
for s in range(1, NUM_SUBJECTS+1):
dist = 0
for i in range(2, NUM_SUBJECTS_IMGS+1):
img = image.Image("orl_faces/s%d/%d.pgm"%(s, i)).mask_ellipse()
d1 = img.find_lbp((0, 0, img.width(), img.height()))
dist += image.match_descriptor(d0, d1)
print("Average dist for subject %d: %d"%(s, dist/NUM_SUBJECTS_IMGS))

img = image.Image("orl_faces/%s/1.pgm"%(SUB)).mask_ellipse()
img = image.Image("orl_faces/s%d/%d.pgm"%(s, i)).mask_ellipse()
我把上面这两句话改成下面这两句，运行时会出现错误，麻烦大佬告诉我哪里出了问题，谢谢。。。。
img = image.Image("C:/Users/wx/Desktop/wx.pgm"%(SUB)).mask_ellipse()
img = image.Image("C:/Users/wx/Desktop%d/%d.pgm"%(s, i)).mask_ellipse()