def demo_ai_camera_speaker(ip):
"""
智能相机的构建，实时识别相机中的物体
间隔一段时间，把识别的物体朗读出来
Parameter
--------
*ip:string
-树莓派的IP
"""
camera = Camera()
camera.connect_server(ip)
camera.start_receive()
ai = Ai()
speaker = Speaker()
interval = 20
times = 0
while True:
pic = camera.take_picture()
ret,names,box= ai.find_object(pic)
cv2.imshow("ai", ret)
cv2.waitKey(1)
times = times + 1
if times > interval:
times = 0
if len(names) > 0:
speaker.say('i find')
for item in names:
speaker.say(item)
if len(names) > 0:
speaker.say('in the picture')
def demo_step_find_object(ip,
speed=20,
dis=1,
object='cup',
vAngle=30,
hAngle=90):
"""
移动，一步一步的寻找物体
Parameter
-------
*ip:string
-树莓派的
*object:string
-要寻找的物体
*vAngle:int
-垂直方向的角度
*hAngle:int
-水平方向的角度
*speed:int
-移动的速度
*dis:float
-时间间隔
"""
# 初始化
car = Car(ip)
# 相机初始化
camera = Camera()
camera.connect_server(ip)
camera.start_receive()
camera.thread_play()
ai = Ai(classes="./aiLib/coco/coco.names",
config="./aiLib/coco/yolov3.cfg",
weight="./aiLib/coco/yolov3.weights")
car.turn_servo_camera_vertical(vAngle)
car.turn_servo_camera_horizental(hAngle)
global STOP_FLAGE
while True:
if STOP_FLAGE is True:
print('over .............................................')
return
status = get_status_with_camera(car, camera, ai, object)
car.turn_servo_camera_horizental(90)
print(status)
if status == 'status_move':
car.run_forward(speed, dis)
if status == 'status_turn_right':
car.spin_right(10, 0.4)
if status == 'status_turn_left':
car.spin_left(10, 0.4)
if status == 'status_stop':
return
def demo_line_ai(ip, speed, dis):
"""
利用训练数据进行巡线
Param
-----
*ip: string
-树莓的ip
*speed: int
-运行速度
*dis: int
-检测一次走的距离
"""
#相机初始化
camera = Camera()
camera.connect_server(ip)
camera.start_receive()
# camera.thread_play()
#车初始化
car = Car(ip)
#Ai初始化，自己训练的结果
ai = Ai()
global STOP_FLAGE
while True:
pic = camera.take_picture() #cv2.imread("./aiLib/line/line.jpg")#
ret, name, box = ai.find_object(pic)
cv2.imshow('test', ret)
cv2.waitKey(1)
# continue
x = 0
if len(name) == 0: #没有检测到线
continue
for item in name:
if item == 'line':
x = box[0][0]
print(x, type(x))
if 250 < x < 380:
car.run_forward(speed, dis) #直行
elif x < 250:
print("spin right")
car.turn_left(speed * 0.6, dis) #左转
elif x > 380:
print("spin left")
car.turn_right(speed * 0.6, dis) #右转
if STOP_FLAGE:
return
def demo_move_step_find_object1(ip,
speed=20,
dis=1,
object='cup',
vAngle=65,
hAngle=90):
"""
连续移动寻找物体
Parameter
-------
*ip:string
-树莓派的Ip
*object:string
-要寻找的物体
*vAngle:int
-垂直方向的角度
*hAngle:int
-水平方向的角度
"""
camera = Camera()
camera.connect_server(ip)
camera.start_receive()
ai = Ai()
mainThread_ = threading.Thread(target=find_object,
args=(
camera,
ai,
object,
))
mainThread_.start() #启动相机查看功能
moveThread_ = threading.Thread(target=move_step_find_object1_thread,
args=(
ip,
camera,
ai,
object,
vAngle,
hAngle,
))
moveThread_.start() #启动寻物
camera.play() #图像显示
def demo_shaking_camera_find_object1(ip, object):
"""
控制相机的舵机寻找物体,让相机上下水平进行旋转，寻找物体
Parameter
---
*object:string
-要寻找的物体
"""
print(type(object))
global STOP_FLAGE
camera = Camera()
camera.connect_server(ip)
camera.start_receive()
camera.thread_play()
car = Car(ip)
ai = Ai()
speaker = Speaker()
for pos in range(25, 55, 15):
car.turn_servo_camera_vertical(pos)
for angle in range(20, 180, 20):
car.turn_servo_camera_horizental(angle)
time.sleep(2) #图像稳定时间
picture = camera.take_picture()
frame, names, _ = ai.find_object(picture)
if STOP_FLAGE:
return
print(names)
for item in names:
if item == object:
speaker.say("find a")
speaker.say(item)
cv2.imshow('result', frame)
cv2.waitKey(0)
return
def demo_line_algrithm(ip, speed, dis):
"""
利用图像传统知识进行巡线,对图像进行二值化，选取组最大的轮廓的中心点。图像的长640，宽480。
0 左转 250 直行 320 直行 380 右转 640
Parameter
--------
* ip:string
-树莓派的IP
* speed:int
-小车运行速度
* dis：float
-运行的时间，控制距离
"""
#相机的初始化
camera = Camera()
camera.connect_server(ip)
camera.start_receive()
camera.thread_play()
#算法初始化
algithm = Algrithm()
#小车初始化
car = Car(ip)
global STOP_FLAGE
while True:
pic = camera.take_picture()
pt = algithm.line(pic, 60)
# algithm.set_debug()
x = pt[0]
print('%d和320比较' % x)
if 250 < x < 380:
car.run_forward(speed, dis) #直行
elif x < 250:
print("spin left")
car.turn_left(speed * 0.6, dis) #左转
elif x > 380:
print("spin right")
car.turn_right(speed * 0.6, dis) #右转
if STOP_FLAGE:
return
def demo_move_find_object(ip, object, vAngle=30, hAngle=90):
"""
连续移动寻找物体
Parameter
-------
*ip:string
-树莓派的Ip
*object:string
-要寻找的物体
*vAngle:int
-垂直方向的角度
*hAngle:int
-水平方向的角度
"""
car = Car(ip)
camera = Camera()
camera.connect_server(ip)
camera.start_receive()
camera.thread_play()
ai = Ai(classes="./aiLib/coco/coco.names",
config="./aiLib/coco/yolov3.cfg",
weight="./aiLib/coco/yolov3.weights")
car.turn_servo_camera_vertical(vAngle)
car.turn_servo_camera_horizental(hAngle)
mainThread_ = threading.Thread(target=find_object,
args=(
camera,
ai,
object,
))
mainThread_.start()
Cruising(car, 6) # 以4的速度进行漫游
def demo_ai_camera(ip):
"""
智能相机的构建，实时识别相机中的物体
Parameter
----
*ip：string
-树莓派的Ip
"""
camera = Camera()
camera.connect_server(ip)
camera.start_receive()
ai = Ai()
while True:
pic = camera.take_picture()
ret, names, box = ai.find_object(pic)
cv2.imshow("ai", ret)
k = cv2.waitKey(1)
if k == 27: # wait for ESC key to exit
cv2.destroyAllWindows()
break
def demo_move_step_find_object(ip,
speed=20,
dis=1,
object='cup',
vAngle=40,
hAngle=80):
"""
连续移动寻找物体
Parameter
-------
*ip:string
-树莓派的Ip
*object:string
-要寻找的物体
*vAngle:int
-垂直方向的角度
*hAngle:int
-水平方向的角度
"""
car = Car(ip)
camera = Camera()
camera.connect_server(ip)
camera.start_receive()
camera.thread_play()
ai = Ai(classes="./aiLib/coco/coco.names",
config="./aiLib/coco/yolov3.cfg",
weight="./aiLib/coco/yolov3.weights")
car.turn_servo_camera_vertical(vAngle)
car.turn_servo_camera_horizental(hAngle)
mainThread_ = threading.Thread(target=find_object,
args=(
camera,
ai,
object,
))
mainThread_.start()
Cruising(car, 4) # 以4的速度进行漫游
car.turn_servo_camera_vertical(vAngle)
car.turn_servo_camera_horizental(hAngle)
global STOP_FLAGE
while CAMERA_FLAGE:
if STOP_FLAGE == True:
car.stop_all_wheels()
print('over .............................................')
return
status = get_status_with_camera(car, camera, ai, object)
car.turn_servo_camera_horizental(90)
print(status)
if status == 'status_move':
car.run_forward(speed, dis)
if status == 'status_turn_right':
car.spin_right(10, 0.4)
if status == 'status_turn_left':
car.spin_left(10, 0.4)
if status == 'status_stop':
return
class cameraFigure():
"""
现在只是针对windows llinux
制作智能相机，识别视野中的物体
"""
global figure
def __init__(self, ip="172.16.10.227"):
"""
初始化，区别coco.names;yolov3.cfg;yolov3.weights文件放在aiLib文件夹中;
启动相机服务
Parameter
--------
--ip string类型，default "172.16.10.227" ，
"""
global figure
figure = Figure()
figure.load_model("model\model.ckpt")
print("init camera")
self.camera = Camera()
self.camera = Camera()
self.camera.connect_server(ip)
self.camera.start_receive()
self.ai = Ai()
self.speaker = Speaker()
def show(self):
"""
获取相机，实时检测，图像显示
"""
global figureImage
cv2.namedWindow('ai')
cv2.setMouseCallback('ai', OnMouseAction)
while True:
figureImage = self.camera.take_picture()
blue = (255, 0, 0) # 18
cv2.rectangle(figureImage, (x1, y1), (x2, y2), blue, 1) # 19
cv2.imshow("ai", figureImage)
cv2.waitKey(1)
# mat = self.figure.convert_mat_to_image(figureImage)
# num = self.figure.find_figure(mat)
# print(num)
def start_thread_ai_camera(self):
"""
启动线程
"""
self.mainThread = threading.Thread(target=self.show)
self.mainThread.start()
@staticmethod
def demo():
"""
制作智能相机
"""
camera = cameraFigure("172.16.10.227")
time.sleep(1)
camera.start_thread_ai_camera()