在原本列程上：
while (1):
img = sensor.snapshot()
clock.tick()
code = kpu.run_yolo2(task_fd, img)
if code:
for i in code:
Cut face and resize to 128×128
a = img.draw_rectangle(i.rect())
face_cut = img.cut(i.x(), i.y(), i.w(), i.h())
face_cut_128 = face_cut.resize(128, 128)
a = face_cut_128.pix_to_ai()
a = img.draw_image(face_cut_128, (0,0))
Landmark for face 5 points
fmap = kpu.forward(task_ld, face_cut_128)
plist = fmap[:]
le = (i.x() + int(plist[0] * i.w() - 10), i.y() + int(plist[1] * i.h()))
re = (i.x() + int(plist[2] * i.w()), i.y() + int(plist[3] * i.h()))
nose = (i.x() + int(plist[4] * i.w()), i.y() + int(plist[5] * i.h()))
lm = (i.x() + int(plist[6] * i.w()), i.y() + int(plist[7] * i.h()))
rm = (i.x() + int(plist[8] * i.w()), i.y() + int(plist[9] * i.h()))
a = img.draw_circle(le[0], le[1], 4)
a = img.draw_circle(re[0], re[1], 4)
a = img.draw_circle(nose[0], nose[1], 4)
a = img.draw_circle(lm[0], lm[1], 4)
a = img.draw_circle(rm[0], rm[1], 4)
align face to standard position
src_point = [le, re, nose, lm, rm]
T = image.get_affine_transform(src_point, dst_point)
a = image.warp_affine_ai(img, img_face, T)
a = img_face.ai_to_pix()
a = img.draw_image(img_face, (128,0))
del (face_cut_128)
calculate face feature vector
fmap = kpu.forward(task_fe, img_face)
feature = kpu.face_encode(fmap[:])
reg_flag = False
scores = []
for j in range(len(record_ftrs)):
score = kpu.face_compare(record_ftrs[j], feature)
scores.append(score)
max_score = 0
index = 0
for k in range(len(scores)):
if max_score < scores[k]:
max_score = scores[k]
index = k
if max_score > ACCURACY:
a = img.draw_string(i.x(), i.y(), (“%s :%2.1f” % (
names[index], max_score)), color=(0, 255, 0), scale=2)
else:
a = img.draw_string(i.x(), i.y(), (“X :%2.1f” % (
max_score)), color=(255, 0, 0), scale=2)
if start_processing:
record_ftr = feature
record_ftrs.append(record_ftr)
start_processing = False
break
fps = clock.fps()
print(“%2.1f fps” % fps)
a = lcd.display(img)
gc.collect()
kpu.memtest()
a = kpu.deinit(task_fe)
a = kpu.deinit(task_ld)
a = kpu.deinit(task_fd)
我在想，实现断电存储就是要将人脸特征信息保存在SD上，所以我利用文件操作，将人脸特信息写进了一个TXT文件夹里边，但是当我想把ta 读出来的时候，我遇到一些问题，因为我将人脸信息64编码写进一个TXT里边的，我读取出来需要转换回二进制，然后存放在 record_ftrs[]列表中， 让拍摄的人脸进行比较score = kpu.face_compare(record_ftrs[j], feature)
，我的读取TXT文件代码：
print(“files:”, uos.listdir(“/sd”)) #列出SD所有文件
with open(“/sd/features.txt”, “r”) as f: #读取SD卡features.txt文件
content = f.read()
#print("read:", content) #打印SD卡features.txt文件
print("f_read:",content)
regex = ure.compile("\#") #以#为标记，拆分features.txt
record_ftrs_64=regex.split(content)
f.close()
print(“num:”, len(record_ftrs_64)) #打印拆分后，字符串数量
print(“split:”, record_ftrs_64)
for u in range(len(record_ftrs_64)):
record_ftrs.append(ubinascii.a2b_base64(record_ftrs_64))
print(record_ftrs)
，
我把这段代码，放在前面一个程序（大循坏）的前面，程序在识别到人的识别报了一个错误
我不知道什么问题，请各位朋友解答，非常感谢。
整个程序：
import sensor
import image
import lcd
import KPU as kpu
import time
from Maix import FPIOA, GPIO
import gc
from fpioa_manager import fm
from board import board_info
import utime
import ure
import ubinascii
import uos
task_fd = kpu.load(0×200000)
task_ld = kpu.load(0×300000)
task_fe = kpu.load(0×400000)
clock = time.clock()
fm.register(board_info.BOOT_KEY, fm.fpioa.GPIOHS0)
key_gpio = GPIO(GPIO.GPIOHS0, GPIO.IN)
start_processing = False
BOUNCE_PROTECTION = 50
def set_key_state(*_):
global start_processing
start_processing = True
utime.sleep_ms(BOUNCE_PROTECTION)
key_gpio.irq(set_key_state, GPIO.IRQ_RISING, GPIO.WAKEUP_NOT_SUPPORT)
lcd.init()
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_hmirror(1)
sensor.set_vflip(1)
sensor.run(1)
anchor = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658, 5.155437,
6.92275, 6.718375, 9.01025) # anchor for face detect
dst_point = [(44, 59), (84, 59), (64, 82), (47, 105),
(81, 105)] # standard face key point position
a = kpu.init_yolo2(task_fd, 0.5, 0.3, 5, anchor)
img_lcd = image.Image()
img_face = image.Image(size=(128, 128))
a = img_face.pix_to_ai()
record_ftr = []
record_ftrs = []
names = [‘Mr.1’, ‘Mr.2’, ‘Mr.3’, ‘Mr.4’, ‘Mr.5’,
‘Mr.6’, ‘Mr.7’, ‘Mr.8’, ‘Mr.9’, ‘Mr.10’]
ACCURACY = 85
record_ftrs_64=[]
print(“files:”, uos.listdir(“/sd”)) #列出SD所有文件
with open(“/sd/features.txt”, “r”) as f: #读取SD卡features.txt文件
content = f.read()
#print("read:", content) #打印SD卡features.txt文件
print("f_read:",content)
regex = ure.compile("\#") #以#为标记，拆分features.txt
record_ftrs_64=regex.split(content)
f.close()
print(“num:”, len(record_ftrs_64)) #打印拆分后，字符串数量
print(“split:”, record_ftrs_64)
for u in range(len(record_ftrs_64)):
record_ftrs.append(ubinascii.a2b_base64(record_ftrs_64))
print(record_ftrs)
while (1):
img = sensor.snapshot()
clock.tick()
code = kpu.run_yolo2(task_fd, img)
if code:
for i in code:
Cut face and resize to 128×128
a = img.draw_rectangle(i.rect())
face_cut = img.cut(i.x(), i.y(), i.w(), i.h())
face_cut_128 = face_cut.resize(128, 128)
a = face_cut_128.pix_to_ai()
a = img.draw_image(face_cut_128, (0,0))
Landmark for face 5 points
fmap = kpu.forward(task_ld, face_cut_128)
plist = fmap[:]
le = (i.x() + int(plist[0] * i.w() - 10), i.y() + int(plist[1] * i.h()))
re = (i.x() + int(plist[2] * i.w()), i.y() + int(plist[3] * i.h()))
nose = (i.x() + int(plist[4] * i.w()), i.y() + int(plist[5] * i.h()))
lm = (i.x() + int(plist[6] * i.w()), i.y() + int(plist[7] * i.h()))
rm = (i.x() + int(plist[8] * i.w()), i.y() + int(plist[9] * i.h()))
a = img.draw_circle(le[0], le[1], 4)
a = img.draw_circle(re[0], re[1], 4)
a = img.draw_circle(nose[0], nose[1], 4)
a = img.draw_circle(lm[0], lm[1], 4)
a = img.draw_circle(rm[0], rm[1], 4)
align face to standard position
src_point = [le, re, nose, lm, rm]
T = image.get_affine_transform(src_point, dst_point)
a = image.warp_affine_ai(img, img_face, T)
a = img_face.ai_to_pix()
a = img.draw_image(img_face, (128,0))
del (face_cut_128)
calculate face feature vector
fmap = kpu.forward(task_fe, img_face)
feature = kpu.face_encode(fmap[:])
reg_flag = False
scores = []
for j in range(len(record_ftrs)):
score = kpu.face_compare(record_ftrs[j], feature)
scores.append(score)
max_score = 0
index = 0
for k in range(len(scores)):
if max_score < scores[k]:
max_score = scores[k]
index = k
if max_score > ACCURACY:
a = img.draw_string(i.x(), i.y(), (“%s :%2.1f” % (
names[index], max_score)), color=(0, 255, 0), scale=2)
else:
a = img.draw_string(i.x(), i.y(), (“X :%2.1f” % (
max_score)), color=(255, 0, 0), scale=2)
if start_processing:
record_ftr = feature
record_ftrs.append(record_ftr)
start_processing = False
break
fps = clock.fps()
print(“%2.1f fps” % fps)
a = lcd.display(img)
gc.collect()
kpu.memtest()
a = kpu.deinit(task_fe)
a = kpu.deinit(task_ld)
a = kpu.deinit(task_fd)
