def main(labels=None,
model_addr="/sd/m.kmodel",
sensor_window=(224, 224),
lcd_rotation=0,
sensor_hmirror=False,
sensor_vflip=False):
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_windowing(sensor_window)
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)
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)
try:
while (True):
img = sensor.snapshot()
t = time.ticks_ms()
fmap = kpu.forward(task, img)
t = time.ticks_ms() - t
plist = fmap[:]
pmax = max(plist)
max_index = plist.index(pmax)
img.draw_string(0,
0,
"%.2f : %s" % (pmax, labels[max_index].strip()),
scale=2)
img.draw_string(0, 200, "t:%dms" % (t), scale=2)
lcd.display(img)
except Exception as e:
raise e
finally:
kpu.deinit(task)
def free():
try:
if FaceReco.is_load:
tmp = kpu.deinit(FaceReco.task_fd)
tmp = kpu.deinit(FaceReco.task_ld)
tmp = kpu.deinit(FaceReco.task_fe)
#t, FaceReco.task_fd = FaceReco.task_fd, None
#del t
#t, FaceReco.task_ld = FaceReco.task_ld, None
#del t
#t, FaceReco.task_fe = FaceReco.task_fe, None
#del t
t, FaceReco.img_face = FaceReco.img_face, None
del t
FaceReco.record_ftr = []
FaceReco.record_ftrs = []
button_io.home_button.disirq()
FaceReco.start_processing = False
FaceReco.is_load = False
gc.collect()
except Exception as e:
print(e) # see py_kpu_deinit error will mp_raise_TypeError
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 free():
#print(HowMany.free)
try:
if HowMany.is_load:
kpu.deinit(HowMany.task)
HowMany.is_load = False
except Exception as e:
print(e) # see py_kpu_deinit error will mp_raise_TypeError
def free():
#print(MaybeIs.free)
try:
if MaybeIs.is_load:
kpu.deinit(MaybeIs.task)
MaybeIs.is_load = False
except Exception as e:
print(e) # see py_kpu_deinit error will mp_raise_TypeError
def cleanup(self):
self.close_recorder()
try:
uos.umount(self._ramdisk_mount_point)
except OSError as e:
print(e)
if self._task:
kpu.deinit(self._task)
self._task = None
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 on_draw(self):
if not self.__initialized:
self.__lazy_init()
try:
while True:
img = sensor.snapshot() # Take an image from sensor
print("progress 4 OK!")
# Run the detection routine
bbox = kpu.run_yolo2(self.task, img)
if bbox:
for i in bbox:
print(i)
img.draw_rectangle(i.rect())
lcd.display(img)
home_button = self.get_system().home_button
# TODO
led_w = self.get_system().led_w
if home_button.value() == 0 and self.but_stu == 1:
if led_w.value() == 1:
led_w.value(0)
else:
led_w.value(1)
self.but_stu = 0
if home_button.value() == 1 and self.but_stu == 0:
self.but_stu = 1
except KeyboardInterrupt:
a = kpu.deinit(task)
sys.exit()
def free():
try:
if FaceReco.is_load:
tmp = kpu.deinit(FaceReco.model)
FaceReco.is_load = False
except Exception as e:
print(e) # see py_kpu_deinit error will mp_raise_TypeError
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 main(labels = None, model_addr="/sd/m.kmodel", lcd_rotation=0, sensor_hmirror=False, sensor_vflip=False):
gc.collect()
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_windowing((224, 224))
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)
if not labels:
raise Exception("no labels.txt")
task = kpu.load(model_addr)
try:
while(True):
img = sensor.snapshot()
t = time.ticks_ms()
fmap = kpu.forward(task, img)
t = time.ticks_ms() - t
plist=fmap[:]
pmax=max(plist)
max_index=plist.index(pmax)
img.draw_string(0,0, "%.2f\n%s" %(pmax, labels[max_index].strip()), scale=2, color=(255, 0, 0))
img.draw_string(0, 200, "t:%dms" %(t), scale=2, color=(255, 0, 0))
lcd.display(img)
except Exception as e:
sys.print_exception(e)
finally:
kpu.deinit(task)
def measure_fps(model_file):
task = kpu.load(model_file)
kpu.set_outputs(task, 0, 1, 1, 2)
clock = time.clock()
fps_ = []
for i in range(20):
img = sensor.snapshot()
clock.tick()
fmap = kpu.forward(task, img)
lcd.display(img, oft=(0, 0))
fps_.append(clock.fps())
average_fps = sum(fps_) / len(fps_)
print(average_fps)
global fps_result
fps_result = average_fps
_ = kpu.deinit(task)
def main():
## main
task, graph, counter, uart = init(threshold=0.5, patience=4)
frame_idx = 0
try:
while (True):
# get image
img = sensor.snapshot().rotation_corr(z_rotation=0.0)
# detect boxes
a = img.pix_to_ai()
code = kpu.run_yolo2(task, img)
# set frame
currF = Frame(frame_idx, img, code)
# calc track
diff_idx = graph.track(currF)
# counting
counter.vanish_update(graph.F_list[-1].bboxes,
graph.F_list[-2].bboxes, graph.is_decrease)
counter.count()
# display on IDE
#img = currF.draw_frames()
#img = img.copy((32, 32, 160, 160))
#img.draw_string(0 ,0, str(counter.counter[LEFT])+","+str(counter.counter[RIGHT]),
#color=(0,255,0), scale=3)
#a = lcd.display(img)
# to Gray
msg = str(counter.counter[LEFT])+ DIV + \
str(counter.counter[RIGHT])+ DIV + str(currF.num_object)
_ = uart.write(msg)
#_ = uart.write(img)
print(counter.counter)
# finalize
frame_idx += 1
time.sleep(0.05)
except Exception as e:
# need delete kpu_task when keyboard interrupt
a = kpu.deinit(task)
del task
gc.collect()
print(e)
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 inference(model_file):
task = kpu.load(model_file)
kpu.set_outputs(task, 0, 1, 1, 2)
clock = time.clock()
while (True):
img = sensor.snapshot()
clock.tick()
fmap = kpu.forward(task, img)
fps = clock.fps()
plist = fmap[:]
pmax = max(plist)
max_index = plist.index(pmax)
a = lcd.display(img, oft=(0, 0))
lcd.draw_string(
0, 128, "%.2f:%s " %
(pmax, labels[max_index].strip()))
_ = kpu.deinit(task)
def measure_latency(model_file):
task = kpu.load(model_file)
kpu.set_outputs(task, 0, 1, 1, 2)
clock = time.clock()
latency_ = []
for i in range(20):
img = sensor.snapshot()
clock.tick()
t1 = time.ticks_us()
fmap = kpu.forward(task, img)
t2 = time.ticks_diff(time.ticks_us(), t1) / 1000
lcd.display(img, oft=(0, 0))
latency_.append(t2)
average_latency = sum(latency_) / len(latency_)
print(average_latency)
global latency_result
latency_result = average_latency
_ = kpu.deinit(task)
dist_str = "%.1f"%(dist)
print("[DISTANCE]: " + dist_str)
img.draw_string(2,47, dist_str,scale=3)
lcd.display(img)
continue
name,dist = get_nearest(feature_list,plist)
#print(clock.fps())
if dist < 50 and name != "exclude": #50 is modified from original value 200
img.draw_rectangle(1,46,222,132,color=br.get_color(0,255,0),thickness=3)
img.draw_string(2,47 +30, "%s"%(name),scale=3)
if old_name != name:
namestring = str(name) + "\n" #UART to StickC
uart_Port.write(namestring) #UART to StickC
# print(name) #modified from original
lcd.display(img)
br.play_sound("/sd/voice/"+name+".wav")
old_name = name
else:
old_name = ''
# output
img.draw_string(2,47, "%.2f "%(dist),scale=3)
lcd.display(img)
kpu.fmap_free(fmap)
except KeyboardInterrupt:
kpu.deinit(task)
sys.exit()
uart_Port.deinit() #UART to StickC
del uart_Port #UART to StickC
#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)
#print(labels_txt)
labels=tuple([str(i) for i in labels_txt.split(",")])
#print(labels)
import time
last = time.ticks_ms()
while True:
try:
#KpuTask = kpu.load(0x5C0000)
KpuTask = kpu.load("/sd/yolov2.kmodel")
kpu.init_yolo2(KpuTask, 0.6, 0.3, 5, anchor)
while True:
#print(time.ticks_ms() - last)
last = time.ticks_ms()
img = camera.get_image()
things = kpu.run_yolo2(KpuTask, img)
if things:
for pos in range(len(things)):
i = things[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(), labels[i.classid()]), color=(0, 255, 0))
## gc.collect() # have bug when reply 3
lcd.display(img)
except KeyboardInterrupt as e:
pass
finally:
kpu.deinit(KpuTask)
#break
color=(255, 0, 0),
scale=2))
greetback = False
a = 0
lcd.display(
imgv.draw_string(0,
5,
" pic: " + str(currentImage) + ".jpg " +
str(score),
color=(255, 250, 250),
scale=1))
img = img.resize(100, 100)
lcd.display(imgv.draw_image(img, 0, 128)) #a = img
del (img)
pd = False
if pd == True:
lcd.display(
image.Image("/sd/videopic/idle_" + str(n) + ".jpg",
copy_to_fb=True))
utime.sleep_ms(10)
pd = True
n += 1
if n >= 68:
n = 0
except Exception as x:
a = kpu.deinit(taskfe)
a = kpu.deinit(task)
a = kpu.deinit(taskkp)
sys.print_exception(x, file="/sd/error.txt")
uart_B.write(str(x) + " " + str(x.args[0]))
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:
kpu.deinit(HowManyTask)
#break
try:
FaceRecoModel = kpu.load(0x2C0000)
kpu.init_yolo2(FaceRecoModel, 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()
img.pix_to_ai()
# Run the detection routine
FaceRecoBbox = kpu.run_yolo2(FaceRecoModel, img)
if FaceRecoBbox:
for i in FaceRecoBbox:
# print(i)
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)
while(True):
clock.tick()
img = sensor.snapshot()
code = kpu.run_yolo2(task, img)
infostr = str(clock.fps()) + ' : '
for i in range(len(classes)):
count[i][idx] = 0
if code:
for i in code:
infostr = infostr + classes[i.classid()][0] + ', '
count[i.classid()][idx] = 1
for i in range(len(classes)):
if sum(count[i]) > avg_len/2:
if classes[i][1]:
uart.write(classes[i][1] + 'gairuyo\r')
print(infostr)
#print(count)
idx = (idx + 1) % avg_len
model = kpu.deinit(task)
uart.deinit ()
del uart
def __del__(self):
_ = kpu.deinit(self._m_fe)
_ = kpu.deinit(self._m_ld)
_ = kpu.deinit(self._m_fd)
sout.value(SOUT)
print('nothing detected')
if (FLAG):
#///人脸识别///#
check_key() #按键检测
check_key2() #按键检测
img = sensor.snapshot() #从摄像头获取一张图片
clock.tick() #记录时刻，用于计算帧率
code = kpu.run_yolo2(task_fd, img) # 运行人脸检测模型，获取人脸坐标位置
if key_pressed2 == 1: #如果检测到按键
print("shifted.")
key_pressed2 = 0 #重置按键状态
FLAG = 0
a = kpu.deinit(task_fe)
a = kpu.deinit(task_ld)
a = kpu.deinit(task_fd)
task = kpu.load('/sd/mask.kmodel')
a = kpu.init_yolo2(task, 0.5, 0.3, 5, anchorMsk) #初始化人脸检测模型
continue
if code: # 如果检测到人脸
faceVector += 1
for i in code: # 迭代坐标框
# Cut face and resize to 128x128
a = img.draw_rectangle(i.rect()) # 在屏幕显示人脸方框
face_cut = img.cut(i.x(), i.y(), i.w(),
i.h()) # 裁剪人脸部分图片到 face_cut
face_cut_128 = face_cut.resize(128,
128) # 将裁出的人脸图片 缩放到128 * 128像素
a = face_cut_128.pix_to_ai() # 将裁出图片转换为kpu接受的格式