#
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
from pyb import UART
from machine import LED
led = LED("LED_BLUE")
for i in range(3):
led.on()
time.sleep_ms(500)
led.
off()
time.sleep_ms(500)
# 鍒濆?嬪寲鎽勫儚澶翠紶鎰熷櫒
sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.GRAYSCALE) # or sensor.GRAYSCALE
sensor.set_framesize(sensor.B128X128) # or sensor.QQVGA (or others)
sensor.set_windowing((92,112))
sensor.skip_frames(10) # Let new settings take affect.
sensor.skip_frames(time = 5000) #绛夊緟5s
# 鍒濆?嬪寲涓插彛
uart=UART(3,115200)
#SUB = "s1"
NUM_SUBJECTS = 3 #鍥惧儚搴撲腑涓嶅悓浜烘暟锛屼竴鍏?3浜?
NUM_SUBJECTS_IMGS = 20 #姣忎汉鏈?20寮犳牱鏈?鍥剧墖
# 鎷嶆憚褰撳墠浜鸿劯銆?
img = sensor.snapshot()
#img = image.Image("singtown/%s/1.pgm"%(SUB))
d0 = img.find_lbp((0, 0, img.width(), img.height()))
#d0涓哄綋鍓嶄汉鑴哥殑lbp鐗瑰緛
img = None
pmin = 999999
num=0
def min(pmin, a, s):
global num
if a<pmin:
pmin=a
num=s
return pmin
for s in range(1, NUM_SUBJECTS+1):
dist = 0
for i in range(2, NUM_SUBJECTS_IMGS+1):
img = image.Image("singtown/s%d/%d.pgm"%(s, i))
d1 = img.find_lbp((0, 0, img.width(), img.height()))
#d1涓虹?瑂鏂囦欢澶逛腑鐨勭?琲寮犲浘鐗囩殑lbp鐗瑰緛
dist += image.match_descriptor(d0, d1)#璁＄畻d0 d1鍗虫牱鏈?鍥惧儚涓庤??妫€娴嬩汉鑴哥殑鐗瑰緛宸?寮傚害銆?
print("Average dist for subject %d: %d"%(s, dist/NUM_SUBJECTS_IMGS))
pmin = min(pmin, dist/NUM_SUBJECTS_IMGS, s)#鐗瑰緛宸?寮傚害瓒婂皬锛岃??妫€娴嬩汉鑴镐笌姝ゆ牱鏈?鏇寸浉浼兼洿鍖归厤銆?
print(pmin)
print(num) # num涓哄綋鍓嶆渶鍖归厤鐨勪汉鐨勭紪鍙枫€?
# 鏍煎紡锛氳捣濮嬪瓧鑺? + 浜虹墿缂栧彿 + 缂栧彿锛?1瀛楄妭锛? + 缁撴潫瀛楄妭
start_byte = 0xAA
end_byte =0x55
data = num
data_packet=bytes([start_byte,num,end_byte])
uart.write(
data_packet)
print("Sent packet with markers:", [start_byte,num,end_byte])
# led = LED(1)
led = LED("LED_RED")
for i in range(3):
led.on()
time.sleep_ms(500)
led.
off()
time.sleep_ms(500)
这个编码乱码要怎么改
本文分享了OpenCV ORL人脸数据集的百度网盘下载链接及提取码，为计算机视觉研究者提供便利。
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