def load():
if MaybeIs.is_load == False:
#print(MaybeIs.load)
MaybeIs.task = kpu.load(0x5C0000)
#task = kpu.load("/sd/0x5C0000_20class.kmodel")
kpu.init_yolo2(MaybeIs.task, 0.5, 0.3, 5, (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658, 5.155437, 6.92275, 6.718375, 9.01025))
MaybeIs.is_load = True
def __lazy_init(self):
err_counter = 0
while 1:
try:
sensor.reset() # Reset sensor may failed, let's try sometimes
break
except Exception:
err_counter = err_counter + 1
if err_counter == 20:
lcd.draw_string(lcd.width() // 2 - 100,
lcd.height() // 2 - 4,
"Error: Sensor Init Failed", lcd.WHITE,
lcd.RED)
time.sleep(0.1)
continue
print("progress 1 OK!")
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA) # QVGA=320x240
sensor.run(1)
print("progress 2 OK!")
self.task = kpu.load(0x300000) # Load Model File from Flash
anchor = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658, 5.155437,
6.92275, 6.718375, 9.01025)
# Anchor data is for bbox, extracted from the training sets.
print("progress 3 OK!")
kpu.init_yolo2(self.task, 0.5, 0.3, 5, anchor)
self.but_stu = 1
self.__initialized = True
def load():
if FaceReco.is_load == False:
FaceReco.model = kpu.load(0x2C0000) # Load Model File from Flash
# Anchor data is for bbox, extracted from the training sets.
kpu.init_yolo2(FaceReco.model, 0.5, 0.3, 5, (1.889, 2.5245, 2.9465, 3.94056, 3.99987,
5.3658, 5.155437, 6.92275, 6.718375, 9.01025))
FaceReco.is_load = True
def main(model_addr=0x300000, lcd_rotation=0, sensor_hmirror=False, sensor_vflip=False):
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_hmirror(sensor_hmirror)
sensor.set_vflip(sensor_vflip)
sensor.run(1)
lcd.init(type=1)
lcd.rotation(lcd_rotation)
lcd.clear(lcd.WHITE)
task = kpu.load(model_addr)
anchors = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658, 5.155437, 6.92275, 6.718375, 9.01025)
kpu.init_yolo2(task, 0.5, 0.3, 5, anchors) # threshold:[0,1], nms_value: [0, 1]
try:
while(True):
img = sensor.snapshot()
t = time.ticks_ms()
objects = kpu.run_yolo2(task, img)
t = time.ticks_ms() - t
if objects:
for obj in objects:
img.draw_rectangle(obj.rect())
img.draw_string(0, 200, "t:%dms" %(t), scale=2)
lcd.display(img)
except Exception as e:
sys.print_exception(e)
finally:
kpu.deinit(task)
def __init__(self,
out_range=10,
ignore_limit=0.02,
hmirror=False,
vflip=False,
lcd_rotation=2,
lcd_mirror=True):
self.pitch = 0
self.roll = 0
self.out_range = out_range
self.ignore = ignore_limit
self.task_fd = kpu.load(0x300000) # face model addr in flash
anchor = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658,
5.155437, 6.92275, 6.718375, 9.01025)
kpu.init_yolo2(self.task_fd, 0.5, 0.3, 5, anchor)
lcd.init()
lcd.rotation(lcd_rotation)
lcd.mirror(lcd_mirror)
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
if hmirror:
sensor.set_hmirror(1)
if vflip:
sensor.set_vflip(1)
def main(anchors, labels=None, model_addr="/sd/m.kmodel"):
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_windowing((224, 224))
sensor.run(1)
lcd.init(type=1)
lcd.clear(lcd.WHITE)
if not labels:
with open('labels.txt', 'r') as f:
exec(f.read())
if not labels:
print("no labels.txt")
img = image.Image(size=(320, 240))
img.draw_string(90, 110, "no labels.txt", color=(255, 0, 0), scale=2)
lcd.display(img)
return 1
try:
img = image.Image("startup.jpg")
lcd.display(img)
except Exception:
img = image.Image(size=(320, 240))
img.draw_string(90,
110,
"loading model...",
color=(255, 255, 255),
scale=2)
lcd.display(img)
task = kpu.load(model_addr)
kpu.init_yolo2(task, 0.5, 0.3, 5,
anchors) # threshold:[0,1], nms_value: [0, 1]
try:
while (True):
img = sensor.snapshot()
t = time.ticks_ms()
objects = kpu.run_yolo2(task, img)
t = time.ticks_ms() - t
if objects:
for obj in objects:
pos = obj.rect()
img.draw_rectangle(pos)
img.draw_string(pos[0],
pos[1],
"%s : %.2f" %
(labels[obj.classid()], obj.value()),
scale=2)
img.draw_string(0, 200, "t:%dms" % (t), scale=2)
lcd.display(img)
except Exception as e:
sys.print_exception(e)
finally:
kpu.deinit(task)
def seeotheritems(): #7second delay
global taskfe
global a
global task
global yolonum
global anchor
classes = [
'aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat',
'chair', 'cow', 'diningtable', 'dog', 'horse', 'motorbike', 'person',
'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor'
]
anchored = (1.08, 1.19, 3.42, 4.41, 6.63, 11.38, 9.42, 5.11, 16.62, 10.52)
kpu.deinit(taskfe)
kpu.deinit(task)
tasktw = kpu.load("/sd/model/20class.kmodel")
uart_B.write(" loaded 20 ")
kpu.init_yolo2(tasktw, 0.5, 0.3, 5, anchored)
imgother = sensor.snapshot()
imgother.pix_to_ai()
detectcode = kpu.run_yolo2(tasktw, imgother)
if detectcode:
led_r.value(0)
led_b.value(0)
for i in detectcode:
imgother = imgother.draw_rectangle(i.rect())
for i in detectcode:
imgother = imgother.draw_string(i.x(),
i.y(),
str(classes[i.classid()]),
color=(255, 250, 250))
imgother = imgother.draw_string(i.x(),
i.y() + 12,
'%f1.3' % i.value(),
color=(255, 250, 250))
imgother.save("/sd/yoloimages/" + str(yolonum) + ".jpg",
quality=70)
utime.sleep_ms(50)
yolonum += 1
uart_B.write(" |Yolo|> " + str(classes[i.classid()]) + " <||")
f = open("/sd/printoutput.txt", "a+")
f.write("Yolo detected: " + str(classes[i.classid()]) + "\n\r")
f.close()
del (imgother)
kpu.deinit(tasktw)
del (tasktw)
gc.collect()
uart_B.write(" killed ")
task = kpu.load("/sd/facedetect.kmodel")
taskfe = kpu.load("/sd/model/FE.smodel")
utime.sleep_ms(10)
led_r.value(1)
led_b.value(1)
kpu.init_yolo2(task, 0.5, 0.3, 5, anchor)
uart_B.write(" restarted ")
def find_face():
lcd.init()
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_vflip(1)
sensor.run(1)
task = kpu.load(0x300000)
anchor = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658, 5.155437,
6.92275, 6.718375, 9.01025)
kpu.init_yolo2(task, 0.5, 0.3, 5, anchor)
while (True):
img = sensor.snapshot()
code = kpu.run_yolo2(task, img)
if code:
for i in code:
img.draw_rectangle(i.rect())
lcd.display(img)
kpu.deinit(task)
def main(model_addr=0x300000,
lcd_rotation=0,
sensor_hmirror=False,
sensor_vflip=False):
try:
sensor.reset()
except Exception as e:
raise Exception(
"sensor reset fail, please check hardware connection, or hardware damaged! err: {}"
.format(e))
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_hmirror(sensor_hmirror)
sensor.set_vflip(sensor_vflip)
sensor.run(1)
lcd.init(type=1)
lcd.rotation(lcd_rotation)
lcd.clear(lcd.WHITE)
anchors = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658, 5.155437,
6.92275, 6.718375, 9.01025)
try:
task = None
task = kpu.load(model_addr)
kpu.init_yolo2(task, 0.5, 0.3, 5,
anchors) # threshold:[0,1], nms_value: [0, 1]
while (True):
img = sensor.snapshot()
t = time.ticks_ms()
objects = kpu.run_yolo2(task, img)
t = time.ticks_ms() - t
if objects:
for obj in objects:
img.draw_rectangle(obj.rect())
img.draw_string(0, 200, "t:%dms" % (t), scale=2)
lcd.display(img)
except Exception as e:
raise e
finally:
if not task is None:
kpu.deinit(task)
def _resetTask():
global g_selCnt
global g_cFiler
global g_task
info = g_cFiler.getInfoList()[g_selCnt]
fullPath = info.dirName + '/' + info.modelName
fullPath = '/sd/models/' + fullPath + '.kmodel'
try:
g_task = kpu.load(fullPath)
if (info.modelType == 'yolo2'):
anchor = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658,
5.155437, 6.92275, 6.718375, 9.01025)
# Anchor data is for bbox, extracted from the training sets.
kpu.init_yolo2(g_task, 0.5, 0.3, 5, anchor)
except:
lcd.draw_string(0, 20, "Err:" + info.modelName + " not find.",
lcd.WHITE, lcd.RED)
g_task = None
return g_task
def init_kpu(threshold=0.3):
classes = ["person"]
task = kpu.load(
0x300000
) #change to "/sd/name_of_the_model_file.kmodel" if loading from SD card
a = kpu.set_outputs(
task, 0, 7, 7, 30
) #the actual shape needs to match the last layer shape of your model(before Reshape)
anchor = (0.57273, 0.677385, 1.87446, 2.06253, 3.33843, 5.47434, 7.88282,
3.52778, 9.77052, 9.16828)
a = kpu.init_yolo2(
task, threshold, 0.3, 5, anchor
) #tweak the second parameter if you're getting too many false positives
return task
def __init__(self):
self.object_detected = None
self.percent = 0
self.classes = ['face']
self.anchor = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658,
5.155437, 6.92275, 6.718375, 9.01025)
self.x_center = 0
self.y_center = 0
self.object_detection_task = kpu.load(0x659000)
a = kpu.set_outputs(self.object_detection_task, 0, 7, 7, 30)
a = kpu.init_yolo2(self.object_detection_task, 0.1, 0.1, 5,
self.anchor)
def Init_Task():
global labels
global objects
objects = kpu.load("/sd/laji.kmodel")
f = open("anchors.txt", "r")
anchor_txt = f.read()
L = []
for i in anchor_txt.split(","):
L.append(float(i))
anchor = tuple(L)
f.close()
a = kpu.init_yolo2(objects, 0.6, 0.3, 5, anchor)
f = open("classes.txt", "r")
labels_txt = f.read()
labels = labels_txt.split(",")
f.close()
def load():
if FaceReco.is_load == False:
FaceReco.task_fd = kpu.load(0x2C0000)
FaceReco.task_ld = kpu.load(0x580000)
FaceReco.task_fe = kpu.load(0x340000)
a = kpu.init_yolo2(FaceReco.task_fd, 0.5, 0.3, 5, anchor)
FaceReco.img_face = image.Image(size=(128, 128))
a = FaceReco.img_face.pix_to_ai()
FaceReco.start_processing = False
from Maix import GPIO
button_io.home_button.irq(
FaceReco.set_key_state, GPIO.IRQ_RISING, GPIO.WAKEUP_NOT_SUPPORT)
FaceReco.is_load = True
def __init__(self, FileName, Classes, Anchor, bool=False):
self.row = global_value.row
global_value.row = global_value.row + 1
self.object_detected = None
self.percent = 0
self.file_name = FileName
self.classes = Classes
self.anchor = Anchor
self.x_center = 0
self.y_center = 0
if bool:
self.object_detected_task = kpu.load(self.file_name)
a = kpu.set_outputs(self.object_detected_task, 0, 7, 7,
5 * (5 + len(self.classes)))
a = kpu.init_yolo2(self.object_detected_task, 0.1, 0.3, 5,
self.anchor)
else:
pass
def __init__(self):
self._m_fd = kpu.load(0x200000)
self._m_ld = kpu.load(0x300000)
self._m_fe = kpu.load(0x400000)
self._anchor = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658,
5.155437, 6.92275, 6.718375, 9.01025)
self._dst_point = [(44, 59), (84, 59), (64, 82), (47, 105), (81, 105)]
self.names = []
self.features = []
_ = kpu.init_yolo2(self._m_fd, 0.5, 0.3, 5, self._anchor)
self.img_face = image.Image(size=(128, 128))
_ = self.img_face.pix_to_ai()
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
# sensor.set_hmirror(1)
sensor.set_vflip(1)
self.show_img_timeout = 5
self._show_img_t = -5
def checkCamera():
global x, y
x = 0
y = 0
showInfo("camera starting", True)
img = image.Image()
try:
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.skip_frames(time=2000)
lcd.rotation(2)
except:
showInfo("camera init failed", False)
return
else:
showInfo("camera init done", True)
try:
task = kpu.load(0x300000)
anchor = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658, 5.155437,
6.92275, 6.718375, 9.01025)
a = kpu.init_yolo2(task, 0.5, 0.3, 5, anchor)
while True:
img = sensor.snapshot()
code = kpu.run_yolo2(task, img)
if code:
for i in code:
a = img.draw_rectangle(i.rect(), color=lcd.BLUE)
new = img.copy(roi=(0, 0, 239, 239))
lcd.display(new)
except:
print('kup load fialed')
while True:
img = sensor.snapshot()
new = img.copy(roi=(0, 0, 239, 239))
lcd.display(new)
#tested with frimware 5-0.22
import sensor,image,lcd
import KPU as kpu
lcd.init()
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_windowing((224, 224))
sensor.set_vflip(1)
sensor.run(1)
classes = ["racoon"]
task = kpu.load(0x200000) #change to "/sd/name_of_the_model_file.kmodel" if loading from SD card
a = kpu.set_outputs(task, 0, 7,7,30) #the actual shape needs to match the last layer shape of your model(before Reshape)
anchor = (0.57273, 0.677385, 1.87446, 2.06253, 3.33843, 5.47434, 7.88282, 3.52778, 9.77052, 9.16828)
a = kpu.init_yolo2(task, 0.3, 0.3, 5, anchor) #tweak the second parameter if you're getting too many false positives
while(True):
img = sensor.snapshot().rotation_corr(z_rotation=90.0)
a = img.pix_to_ai()
code = kpu.run_yolo2(task, img)
if code:
for i in code:
a=img.draw_rectangle(i.rect(),color = (0, 255, 0))
a = img.draw_string(i.x(),i.y(), classes[i.classid()], color=(255,0,0), scale=3)
a = lcd.display(img)
else:
a = lcd.display(img)
a = kpu.deinit(task)
uart = UART(UART.UART1, 115200, 8, None, 1, timeout=1000,
read_buf_len=4096) #配置uart
lcd.init() # 初始化lcd
lcd.rotation(2)
sensor.reset() #初始化sensor 摄像头
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_hmirror(0) #设置摄像头镜像
sensor.set_vflip(0) #设置摄像头翻转
sensor.run(1) #使能摄像头
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 用于人脸检测的Anchor
dst_point = [
(44, 59), (84, 59), (64, 82), (47, 105), (81, 105)
] #standard face key point position 标准正脸的5关键点坐标 分别为 左眼 右眼 鼻子 左嘴角 右嘴角
a = kpu.init_yolo2(task_fd, 0.5, 0.3, 5, anchor) #初始化人脸检测模型
img_lcd = image.Image() # 设置显示buf
img_face = image.Image(size=(128, 128)) #设置 128 * 128 人脸图片buf
a = img_face.pix_to_ai() # 将图片转为kpu接受的格式
record_ftr = [] #空列表 用于存储当前196维特征
record_ftrs = [] #空列表 用于存储按键记录下人脸特征， 可以将特征以txt等文件形式保存到sd卡后，读取到此列表，即可实现人脸断电存储。
names = [] # 人名标签，与上面列表特征值一一对应。
with open("/sd/recordftr3.txt", "r") as f:
while (1):
line = f.readline()
if not line:
break
name = line[0:line.index('#')]
line = line[line.index('#') + 1:]
record_ftrs.append(eval(line))
names.append(name)
if err_counter == 20:
lcd.draw_string(lcd.width() // 2 - 100,
lcd.height() // 2 - 4, "Error: Sensor Init Failed",
lcd.WHITE, lcd.RED)
time.sleep(0.1)
continue
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA) #QVGA=320x240
sensor.run(1)
task = kpu.load(0x300000) # Load Model File from Flash
anchor = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658, 5.155437, 6.92275,
6.718375, 9.01025)
# Anchor data is for bbox, extracted from the training sets.
kpu.init_yolo2(task, 0.5, 0.3, 5, anchor)
but_stu = 1
try:
while (True):
img = sensor.snapshot() # Take an image from sensor
bbox = kpu.run_yolo2(task, img) # Run the detection routine
if bbox:
bbox.sort(reverse=True, key=lambda x: x.rect()[2] * x.rect()[3])
c = bbox[0].rect()[0] + (bbox[0].rect()[2] / 2)
print(str(c) + ' ' + str(len(bbox)))
if c < 120:
print('>>>')
u_send(200)
if c > 160:
lcd.init()
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_windowing((224, 224))
sensor.set_vflip(1)
sensor.run(1)
fm.register(board_info.PIN15, fm.fpioa.UART1_TX)
fm.register(board_info.PIN17, fm.fpioa.UART1_RX)
uart_A = UART(UART.UART1, 115200, 8, None, 1, timeout=1000, read_buf_len=4096)
classes = ["racoon"]
task = kpu.load(0x600000)
anchor = (0.57273, 0.677385, 1.87446, 2.06253, 3.33843, 5.47434, 7.88282,
3.52778, 9.77052, 9.16828)
a = kpu.init_yolo2(task, 0.3, 0.3, 5, anchor)
while (True):
img = sensor.snapshot()
#.rotation_corr(z_rotation=90.0)
#a = img.pix_to_ai()
code = kpu.run_yolo2(task, img)
if code:
for i in code:
a = img.draw_rectangle(i.rect(), color=(0, 255, 0))
a = img.draw_string(i.x(),
i.y(),
classes[i.classid()],
color=(255, 0, 0),
scale=3)
uart_A.write(str(i.rect()))
a = lcd.display(img)
import camera
import KPU as kpu
if __name__ == "__main__":
import time
last = time.ticks_ms()
classes = ['aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat', 'chair', 'cow', 'diningtable', 'dog', 'horse', 'motorbike', 'person', 'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor']
while True:
try:
HowManyTask = kpu.load(0x5C0000)
#task = kpu.load("/sd/0x5C0000_20class.kmodel")
kpu.init_yolo2(HowManyTask, 0.5, 0.3, 5, (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658, 5.155437, 6.92275, 6.718375, 9.01025))
while True:
#print(time.ticks_ms() - last)
last = time.ticks_ms()
img = camera.obj.get_image()
HowManyThings = kpu.run_yolo2(HowManyTask, img)
if HowManyThings:
for pos in range(len(HowManyThings)):
i = HowManyThings[pos]
img.draw_rectangle(320 - (i.x() + i.w()), i.y(), i.w(), i.h())
img.draw_string(320 - (i.x() + i.w()), i.y(), '%.2f:%s' % (i.value(), classes[i.classid()]), color=(0, 255, 0))
## gc.collect() # have bug when reply 3
lcd.display(img)
except KeyboardInterrupt as e:
pass
finally:
def main():
servo_freq = 50 # Hz
servo_vert = Servo(pin=10,
freq=servo_freq,
min_duty=7,
max_duty=11.5,
timer=Timer.TIMER0,
channel=Timer.CHANNEL0,
initial_pos=0.5)
servo_hor = Servo(pin=11,
freq=servo_freq,
min_duty=2.8,
max_duty=11.5,
timer=Timer.TIMER0,
channel=Timer.CHANNEL1)
lcd.init(freq=15000000)
lcd.direction(lcd.YX_LRDU)
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_vflip(1)
# 20 class yolo
classes = [
'aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat',
'chair', 'cow', 'diningtable', 'dog', 'horse', 'motorbike', 'person',
'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor'
]
# target_class = 14 # person
# target_class = 7 # cat
target_class = 4 # bottle
# target_class = 19 # monitor
task = kpu.load(0x500000)
anchor = (1.08, 1.19, 3.42, 4.41, 6.63, 11.38, 9.42, 5.11, 16.62, 10.52)
# For face detector yolo
# task = kpu.load(0x300000)
# anchor = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658, 5.155437, 6.92275, 6.718375, 9.01025)
# target_class = 0
a = kpu.init_yolo2(task, 0.1, 0.3, 5, anchor)
sensor.run(1)
while (True):
img = sensor.snapshot()
code = kpu.run_yolo2(task, img)
target_boxes = []
if code:
target_boxes = [d for d in code if d.classid() == target_class]
if target_boxes:
# change turret position
target = max(target_boxes, key=lambda d: d.value())
a = img.draw_rectangle(target.rect())
a = lcd.display(img)
for i in code:
lcd.draw_string(target.x(),
target.y() + 12, '%f1.3' % target.value(),
lcd.RED, lcd.WHITE)
target_center_x = target.x() + target.w() // 2
target_center_y = target.y() + target.h() // 2
servo_hor.pos += 0.00015 * (sensor.width() // 2 - target_center_x)
servo_vert.pos -= 0.0005 * (sensor.height() // 2 - target_center_y)
# print('hor', servo_hor.pos)
# print('vert', servo_vert.pos)
else:
a = lcd.display(img)
kpu.deinit(task)
class Maix_dock_device:
TOF10120_addr = 0x52
VL53L0X_addr = 0x29
memaddr = 0xc2
nbytes = 1
VL53L0X_REG_IDENTIFICATION_MODEL_ID = 0xc0
VL53L0X_REG_IDENTIFICATION_REVISION_ID = 0xc2
VL53L0X_REG_RESULT_INTERRUPT_STATUS = 0x13
VL53L0X_REG_RESULT_RANGE_STATUS = 0x14
VL53L0X_REG_SYSRANGE_START = 0x00
pcf8591_addr = 0x48
#pcf8591_addr = 0x4f
fm.register(1, fm.fpioa.GPIO0)
fm.register(2, fm.fpioa.GPIO1)
fm.register(3, fm.fpioa.GPIO2)
fm.register(13, fm.fpioa.GPIO3)
fm.register(14, fm.fpioa.GPIO4)
fm.register(15, fm.fpioa.GPIOHS1)
fm.register(17, fm.fpioa.GPIOHS2)
UVC = GPIO(GPIO.GPIO0, GPIO.OUT)
LED_dis = GPIO(GPIO.GPIO1, GPIO.OUT)
BEE = GPIO(GPIO.GPIO2, GPIO.OUT)
TEMP_1 = GPIO(GPIO.GPIO3, GPIO.OUT)
TEMP_2 = GPIO(GPIO.GPIO4, GPIO.OUT)
KEY_start = GPIO(GPIO.GPIOHS1, GPIO.IN, GPIO.IRQ_FALLING)
#key = GPIO(GPIO.GPIOHS0, GPIO.IN, GPIO.PULL_NONE)
KEY_lock = GPIO(GPIO.GPIOHS2, GPIO.IN, GPIO.PULL_NONE)
tempBorder_times = 0
#lcd.init()
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.run(1)
task = kpu.load(
0x300000
) # you need put model(face.kfpkg) in flash at address 0x300000
# task = kpu.load("/sd/face.kmodel")
anchor = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658, 5.155437,
6.92275, 6.718375, 9.01025)
a = kpu.init_yolo2(task, 0.5, 0.3, 5, anchor)
i2c = I2C(I2C.I2C0, mode=I2C.MODE_MASTER, freq=100000, scl=9,
sda=10) # software i2c
i2c_extend = I2C(I2C.I2C1,
mode=I2C.MODE_MASTER,
freq=100000,
scl=11,
sda=12) # software i2c
def __init__(self):
print("Maix_dock_device class")
self.infrared_range_left = 0
self.infrared_range_right = 0
self.temperature_sensor_left = 0
self.temperature_sensor_right = 0
self.ad48v = 0
self.face_detection = 0
self.readAdd_times = 0
def set_face_detection(self):
img = sensor.snapshot()
code = kpu.run_yolo2(self.task, img)
if code:
for i in code:
#print(i)
a = img.draw_rectangle(i.rect())
print("find face")
self.face_detection = 1
else:
print("no face")
self.face_detection = 0
def get_face_detection(self):
return self.face_detection
def get_infrared_range_left(self):
return self.infrared_range_left
def get_infrared_range_right(self):
return self.infrared_range_right
def get_ad48v(self):
return self.ad48v
def get_temperature_sensor_left(self):
return self.temperature_sensor_left
def get_temperature_sensor_left(self):
return self.temperature_sensor_left
def set_UVC_OUT(self, value):
self.UVC.value(value)
def set_led(self, value):
self.LED_dis.value(value)
def get_temperature_sensor_left(self):
return 20.1
def get_keyValue_start(self):
if (self.KEY_start.value() == 1):
time.sleep_ms(10)
if (self.KEY_start.value() == 1):
#print("KEY_start close")
return 1
else:
#print("KEY_start open")
return 0
def show_deviceAddr(self):
devices = self.i2c.scan()
print(devices)
devices2 = self.i2c_extend.scan()
print(devices2)
def set_infrared_range_left(self):
try:
self.i2c.writeto_mem(0x29, 0x00, chr(1))
time.sleep_ms(10)
#time.sleep_ms(40)
data_i2c = self.i2c.readfrom_mem(0x29, 0x1e, 2)
data_i2c = data_i2c[0] << 8 | data_i2c[1]
if data_i2c != 20:
self.infrared_range_left = data_i2c
return data_i2c
else:
print("data_i2c == 20")
return None
except OSError as err:
if err.args[0] == errno.EIO:
print("i2c1 dis errno.EIO")
return None
else:
print("i2c1 abnormal")
return None
def set_infrared_range_right(self):
try:
self.i2c_extend.writeto_mem(0x29, 0x00, chr(1))
time.sleep_ms(10)
#time.sleep_ms(40)
data_i2c = self.i2c_extend.readfrom_mem(0x29, 0x1e, 2)
data_i2c = data_i2c[0] << 8 | data_i2c[1]
if data_i2c != 20:
self.infrared_range_right = data_i2c
return data_i2c
else:
print("data_i2c == 20")
return None
except OSError as err:
if err.args[0] == errno.EIO:
print("i2c2 errno.EIO")
return None
else:
print("i2c2 abnormal")
return None
def set_ad48v_chl(self, chn):
try:
if chn == 0:
self.i2c.writeto(self.pcf8591_addr, chr(0x40))
self.i2c.readfrom(self.pcf8591_addr, 1)
ad_value = self.i2c.readfrom(self.pcf8591_addr, 1)
ad_value = ad_value[0] * 58 / 255
self.ad48v = ad_value - 1.2
return ad_value
if chn == 1:
self.i2c.writeto(self.pcf8591_addr, chr(0x41))
self.i2c.readfrom(self.pcf8591_addr, 1)
ad_value = self.i2c.readfrom(self.pcf8591_addr, 1)
ad_value = 3.3 * ad_value[0] / 255
self.ad48v = -61.44 * ad_value + 174.4
return ad_value
if chn == 2:
self.i2c.writeto(self.pcf8591_addr, chr(0x42))
self.i2c.readfrom(self.pcf8591_addr, 1)
ad_value = self.i2c.readfrom(self.pcf8591_addr, 1)
ad_value = 3.3 * ad_value[0] / 255
self.ad48v = -61.44 * ad_value + 174.4
return ad_value
if chn == 3:
self.i2c.writeto(self.pcf8591_addr, chr(0x43))
except OSError as err:
if err.args[0] == errno.EIO:
print("i2c1 ad errno.EIO")
def set_ad48v(self, chn):
self.set_ad48v_chl(chn)
def set_tof10120_left(self):
try:
data_i2c = self.i2c.readfrom_mem(self.TOF10120_addr, 0x00, 2)
dis_left = data_i2c[0] * 256 + data_i2c[1]
print("dis_left", '%d' % dis_left)
except OSError as err:
if err.args[0] == errno.EIO:
print("i2c1 tof10120_left errno.EIO")
def set_tof10120_right(self):
try:
data_i2c = self.i2c.readfrom_mem(self.TOF10120_addr + 1, 0x00, 2)
dis_right = data_i2c[0] * 256 + data_i2c[1]
print("dis_left", '%d' % dis_right)
except OSError as err:
if err.args[0] == errno.EIO:
print("i2c1 tof10120_right errno.EIO")
def uvc_autoControl(self):
tempBorder_times = 0
if self.readAdd_times == 0:
self.readAdd_times += 1
self.show_deviceAddr()
self.set_infrared_range_left()
utime.sleep_ms(200)
self.set_ad48v(0)
utime.sleep_ms(200)
self.set_infrared_range_right()
utime.sleep_ms(200)
self.set_face_detection()
if self.get_keyValue_start():
if ((self.get_face_detection() == 0) and (self.get_ad48v(0) > 36)):
if ((tempBorder_times <= 3)
and ((self.get_infrared_range_left() < 500) or
(self.get_infrared_range_right() < 500))):
self.set_UVC_OUT(1)
self.set_led(1)
print("uvc_out: 1")
else:
self.set_UVC_OUT(0)
self.set_led(0)
print("uvc_out: 0")
print("key_start_down!")
else:
print("key_start_up!")
self.set_UVC_OUT(0)
self.set_led(0)
print("infrared_range_left = ", self.get_infrared_range_left())
print("infrared_range_right = ", self.get_infrared_range_right())
print("ad48v = ", self.get_ad48v())
print("face_detection = ", self.get_face_detection())
self.set_ad48v(1)
tempBorder1 = self.get_ad48v()
print("temp_left = ", tempBorder1)
self.set_ad48v(2)
tempBorder2 = self.get_ad48v()
print("temp_right = ", tempBorder2)
if (tempBorder1 > 70 or tempBorder2 > 70):
tempBorder_times += 1
if (tempBorder_times > 3):
tempBorder_times = 4
else:
tempBorder_times = 0
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
while (1):
img = sensor.snapshot()
clock.tick()
def load():
if FaceDetect.is_load == False:
FaceDetect.model = kpu.load(0x2C0000) # Load Model File from Flash
# Anchor data is for bbox, extracted from the training sets.
kpu.init_yolo2(FaceDetect.model, 0.5, 0.3, 5, anchor)
FaceDetect.is_load = True
img_w = sensor.width()
img_h = sensor.height()
sensor_ID = sensor.get_id()
if (sensor_ID == 30530):
sensor_ID_str = 'OV7740'
print("image sensor is " + str(sensor_ID_str) + ", with size " + str(img_w) +
" x " + str(img_h))
sensor.skip_frames(time=600)
#sensor.run(1)
#https://maixpy.sipeed.com/zh/libs/Maix/kpu.html
task = kpu.load(0x300000) # Load Model File from Flash
#you need put model(face.kfpkg) in flash at address 0x300000
anchor = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658, 5.155437, 6.92275,
6.718375, 9.01025)
# Anchor data is for bbox, extracted from the training sets.
kpu.init_yolo2(task, 0.5, 0.3, 5,
anchor) # kpu 网络对象,threshold,box_iou 门限,锚点数,锚点参数与模型参数一致
fps = 0
but_stu = 1
autosave_cnt = 0
face_duration_cnt = 0
clock = time.clock()
gc.collect()
RGB_LED_OFF()
try:
while (True):
clock.tick()
img = sensor.snapshot() # Take an image from sensor
bbox = kpu.run_yolo2(task, img) # Run the detection routine
if bbox:
RGB_LED_RED()
for i in bbox:
f = open(file_name,"a")
str_list_target = ["{:0.4f}".format(x) for x in data]
str_target = ','.join(str_list_target)
f.write(str_target)
f.close()
print("save to dataset success")
def send_sheet(face_id):
return
#=== AI Models ===#
task_face_detect = kpu.load(0x200000)
task_face_encode = kpu.load(0x300000)
kpu.set_outputs(task_face_encode,0,1,1,128)
anchor = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658, 5.155437, 6.92275, 6.718375, 9.01025)
kpu.init_yolo2(task_face_detect, 0.5, 0.3, 5, anchor)
#====== config ======#
face_threshold = 15
dataset_filename = "faces.csv"
#====================#
#=== SETUP ===#
#clear_dataset(dataset_filename,face_dataset)
face_dataset = read_dataset(dataset_filename);
corgi85.IFTTT_init("corgi_detect","0hI55mQkUiimG6RIjpWhp")
#=== wait wifi connect ===#
while corgi85.wifi_check() == 0:
print("WIFI Connecting ...")
time.sleep(1)
import sensor,image,lcd,time
import KPU as kpu
sensor.reset(freq=24000000,dual_buff=True)
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_windowing((320, 224))
sensor.set_vflip(1)
sensor.run(1)
lcd.init(type=2, freq=20000000, color=lcd.BLACK)
#lcd.rotation(2)
classes = ["face", "face_mask"]
task = kpu.load(0x400000)
a = kpu.set_outputs(task, 0, 10,7,35)
anchor = (0.212104,0.261834, 0.630488,0.706821, 1.264643,1.396262, 2.360058,2.507915, 4.348460,4.007944)
a = kpu.init_yolo2(task, 0.5, 0.5, 5, anchor)
while(True):
timestamp = time.ticks_ms()
img = sensor.snapshot()
a = img.pix_to_ai()
faces = kpu.run_yolo2(task, img)
if faces:
for face in faces:
if face.classid() == 0 :
a=img.draw_rectangle(face.rect(),color = (255, 0, 0),thickness=5)
elif face.classid() == 1 :
a=img.draw_rectangle(face.rect(),color = (0,255, 0),thickness=5)
a = img.draw_string(70,10,"FPS : %.2f" % (1000/(time.ticks_ms()-timestamp)),color=(0,255,0),scale=2)
a = lcd.display(img)
a = kpu.deinit(task)
sensor.skip_frames(time=2000) # Wait for settings take effect.
sensor.set_vflip(1)
sensor.set_hmirror(1)
clock = time.clock() # Create a clock object to track the FPS.
print('loading face detect model')
task_detect_face = kpu.load(0x300000) # Charge face detect model into KPU
print('loading face expresion classify model')
task_classify_face = kpu.load(
0x500000) # Charge face classification model into KPU
a = kpu.set_outputs(task_classify_face, 0, 1, 1, 2)
anchor = (1.889, 2.5245, 2.9465, 3.94056, 3.99987, 5.3658, 5.155437, 6.92275,
6.718375, 9.01025)
a = kpu.init_yolo2(task_detect_face, 0.5, 0.3, 5, anchor)
labels = ['happy', 'sad'] # Facial expression labels
print('configuration complete')
while (True):
clock.tick() # Update the FPS clock.
img = sensor.snapshot() # Take a picture and return the image.
detected_face = kpu.run_yolo2(task_detect_face, img)
if detected_face:
for i in detected_face:
face = img.cut(i.x(), i.y(), i.w(), i.h())
face_128 = face.resize(128, 128)
a = face_128.pix_to_ai()