def __init__(self, categoryname=[], samplesnumber=15, bool=False):
self.row = global_value.row
global_value.row = global_value.row + 1
try:
del self.model
except Exception:
pass
try:
del self.classifier
except Exception:
pass
self.classnumber = len(categoryname)
self.samplesnumber = samplesnumber
self.categoryname = categoryname
self.img_copy = None
self.cap_num = 0
self.train_status = 0
self.class_list = []
self.percent = 0
self.image_class = 0
if bool:
self.model = kpu.load(0x514000)
self.classifier = kpu.classifier(self.model, self.classnumber,
self.samplesnumber)
else:
pass
class_num = 3
sample_num = 15
THRESHOLD = 11
class_names = ['class1', 'class2', 'class3']
try:
del model
except Exception:
pass
try:
del classifier
except Exception:
pass
gc.collect()
model = kpu.load(0x300000)
classifier = kpu.classifier(model, class_num, sample_num)
cap_num = 0
train_status = 0
last_cap_time = 0
last_btn_status = 1
while 1:
img = sensor.snapshot()
# capture img
if train_status == 0:
if key.value() == 0:
time.sleep_ms(30)
if key.value() == 0 and (last_btn_status == 1) and (time.ticks_ms() - last_cap_time > 500):
last_btn_status = 0
last_cap_time = time.ticks_ms()
if cap_num < class_num: