def on_removeSubview(self, view):
myDebug(self.__class__.__name__, get_current_function_name())
if view.isFocused:
self.setFocusedView(None)
self.mLastViewList = self.mViewList.copy()
view_ind = self.mViewList.index(view)
input_flow = self.mViewList[view_ind].getInputFlow()
camera_controller = MainController.getController().mCameraController
robot_controller = MainController.getController().mRobotController
if type(input_flow) is CameraInterface:
camera_controller.releaseCamera(input_flow.getID())
elif type(input_flow) is RobotEpuck:
robot_controller.releaseRobot(input_flow)
self.mViewList.pop(self.mViewList.index(view))
self.reLayoutView()
def slot_add_EPuck(self):
dialog = QInputDialog(self)
dialog.setModal(True)
dialog.setStyleSheet("""
background-color: rgba(0, 0, 0, 200);
border:1px solid rgba(0, 200, 200, 150);
""")
dialog.setFixedSize(350, 250)
dialog.setWindowTitle('Set Input Flow for Improcessor')
dialog.setInputMode(QInputDialog.TextInput)
dialog.setLabelText('请输入……（机器人的ip）')
dialog.setTextValue('192.168.3.5')
dialog.setOkButtonText('Ok')
dialog.setCancelButtonText('Cancel')
if dialog.exec_() == QDialog.Accepted:
ip = dialog.textValue()
robot_controller = MainController.getController().mRobotController
robot_controller.addRobot(RobotEpuck)
robot = robot_controller.getRobot(-1)
robot.connect(ip)
view = RobotFrame(self)
view.setRobot(robot)
self.addSubview(view)
else:
print("dialog canceled")
dialog.show()
def mkQMenu(self):
myDebug(self.__class__.__name__, get_current_function_name())
menu=QMenu(self)
menu.setStyleSheet("""
color: rgb(0, 243, 255);
background-color: rgba(255, 255, 255, 0);
border:2px solid rgb(0, 108, 255);
selection-background-color: rgba(183, 212, 255, 150);
"""
)
camera_list = QMenu(menu)
camera_list.setTitle('新建相机视图')
controller = MainController.getController()
camera_names, camera_types = controller.mCameraController.getAvailableCameraNames()
for ind, name in enumerate(camera_names):
cam_action = QAction(name, camera_list)
# cam_action.triggered.connect(self.mCameregister[ind])
cam_action.triggered.connect(partial(self.on_add_camera_view, ind, camera_types[ind]))
camera_list.addAction(cam_action)
menu.addMenu(camera_list)
add_image_proc_action = QAction('添加图像处理视图', menu)
add_image_proc_action.triggered.connect(self.slot_add_image_proc_view)
menu.addAction(add_image_proc_action)
add_robot_action = QAction('添加机器人', menu)
add_robot_action.triggered.connect(self.slot_add_robot)
menu.addAction(add_robot_action)
clear_views_action = QAction('清空视图', menu)
clear_views_action.triggered.connect(self.slot_clearSubview)
menu.addAction(clear_views_action)
return menu
def slot_clearSubview(self):
myDebug(self.__class__.__name__, get_current_function_name())
self.mLastViewList = self.mViewList.copy()
self.mViewList = []
self.reLayoutView()
camera_controller = MainController.getController().mCameraController
for i in self.mLastViewList:
i.destroy()
camera_controller.releaseAllCamera()
self.setFocusedView(None)
def main():
app = QApplication(sys.argv)
XSetting.XSetting.loadSettingFile()
if XSetting.XSetting.isDebug.isPrintDebug:
Test.UnitTest()
print('Load mainController')
mainController = MainController.MainController()
MainController.__controller = mainController
mainController.start()
sys.exit(app.exec_())
def __init__(self, *arg):
myDebug(self.__class__.__name__, get_current_function_name())
super().__init__(*arg)
self.controller = MainController.getController()
self.robot_controller = RobotController.RobotController()
self.robot_controller.start()
self.mDataHandle = DataHandle()
self.controller.addDataHandle(self.mDataHandle)
self.mLayout.addWidget(self.mDataHandle.image_label)
self.mDataHandle.image_label.show()
self.mRobotPolicy = None
def on_add_camera_view(self, cam_id: int, cam_type: XCameraType):
myDebug(self.__class__.__name__, get_current_function_name())
camera_controller = MainController.getController().mCameraController
camera = camera_controller.getCamera(cam_id)
if camera and camera.isOpen():
print('该相机已经打开')
else:
camera_controller.startCamera(cam_id, cam_type)
view = CameraViewFrame(self)
view.setCamera(camera_controller.mCameraList[len(camera_controller.mCameraList) - 1])
self.addSubview(view)
print('打开第%d个相机'%cam_id)
def __init__(self, *args):
myDebug(self.__class__.__name__, get_current_function_name())
super(ImageProcViewBase, self).__init__(*args)
self.mActiveBorderStyle = 'border:1px solid rgba(200, 50, 50, 255);'
self.mUnactiveBorderStyle = 'border:1px solid rgba(200, 200, 200, 150);'
self.deactive()
self.mImageSaveDir = "./general_image_save"
self.mImageHandle = ImageHandle()
self.mImageHandle.setImageSaveDir(self.mImageSaveDir)
self.controller = MainController.getController()
self.controller.addImageHandle(self.mImageHandle)
self.mLayout.addWidget(self.mImageHandle.image_label)
self.mImageHandle.image_label.show()
def __init__(self, *args):
myDebug(self.__class__.__name__, get_current_function_name())
super(ImageProcViewBase, self).__init__(*args)
self.mLayout = QGridLayout(self)
self.mLayout.setContentsMargins(0, 0, 0, 0)
self.setLayout(self.mLayout)
self.mActiveBorderStyle = 'border:1px solid rgba(200, 50, 50, 255);'
self.mUnactiveBorderStyle = 'border:1px solid rgba(200, 200, 200, 150);'
self.deactive()
self.mImageHandle = ImageHandle()
self.controller = MainController.getController()
self.controller.addImageHandle(self.mImageHandle)
self.mLayout.addWidget(self.mImageHandle.image_label)
self.mImageHandle.image_label.show()
def process(self, image: np.ndarray) -> np.ndarray:
ret = super().process(image)
# print(self.channels(image))
if self.channels(image) == 1:
pass
elif self.channels(image) == 3:
pass
elif self.channels(image) == 4:
image_tmp = image[:, :, 0:3]
'''
再此处添加算法，例如：
image_tmp = 255 - image_tmp
'''
image_tmp = image_tmp.astype(np.uint8)
frame = None
if not self.mapInited:
ret = initMap(image_tmp,
ratio=(self.mapheight / self.mapwidth))
if ret:
self.mapBfTrans = ret[0]
self.mapAfTrans = ret[1]
self.transM = ret[2]
self.mapInited = 1
else:
if self.arucodetect:
# 单个二维码测试耗时< 10 ms
frame, self.carIds, self.posiCar, self.poseCar = qrDextbyArUco(
image_tmp, self.transM, self.mapwidth, self.mapheight)
if frame is not None:
image[:, :, 0:3] = frame[:, :, :]
else:
image[:, :, 0:3] = image_tmp[:, :, :]
ret = image
controller = MainController.getController()
if self.carIds:
for i in range(len(self.carIds)):
controller.mCameraData.setData(
'GlobalLocation', self.carIds[i][0],
np.concatenate((self.posiCar[i], self.poseCar[i])))
# print(controller.mCameraData.data)
else:
raise Exception('图像类型不支持')
return ret
def process(self, image: np.ndarray) -> np.ndarray:
ret = super().process(image)
# print(self.channels(image))
if self.channels(image) == 1:
pass
elif self.channels(image) == 3:
pass
elif self.channels(image) == 4:
image_tmp = image[:, :, 0:3]
'''
再此处添加算法，例如：
image_tmp = 255 - image_tmp
'''
controller = MainController.getController()
if controller.mCameraController.mModelYolo is not None:
image_tmp = detect(image_tmp)
else:
print('Yolo model is not loaded')
image[:, :, 0:3] = image_tmp[:, :, :]
ret = image
else:
raise Exception('图像类型不支持')
return ret
def queryGlobalLocation(self):
controller = MainController.getController()
data_tmp = controller.mCameraData.getData('GlobalLocation', self.mId)
if data_tmp is not None:
data = np.array(controller.mCameraData.getData('GlobalLocation', self.mId), dtype=np.float)
self.setSelfPos(data)
def slot_return(self):
myDebug(self.__class__.__name__, get_current_function_name())
controller = MainController.getController()
camera_controller = controller.mCameraController
camera_controller.releaseAllCamera()
self.mFrameViewArea.slot_clearSubview()
def detect(image: np.array):
img0 = image
controller = MainController.getController()
# Initialize
device = select_device()
half = device.type != 'cpu' # half precision only supported on CUDA
# Load model
model = controller.mCameraController.mModelYolo # load FP32 model
stride = int(model.stride.max()) # model stride
imgsz = check_img_size(IMG_SIZE, s=stride) # check img_size
if half:
model.half() # to FP16
img = letterbox(img0, imgsz, stride=stride)[0]
img = img[:, :, ::-1].transpose(2, 0, 1) # BGR to RGB, to 3x416x416
img = np.ascontiguousarray(img)
# Get names and colors
names = model.module.names if hasattr(model, 'module') else model.names
colors = controller.mCameraController.mModelYoloColors
# Run inference
if device.type != 'cpu':
model(
torch.zeros(1, 3, imgsz, imgsz).to(device).type_as(
next(model.parameters()))) # run once
## main
img = torch.from_numpy(img).to(device)
img = img.half() if half else img.float()
img /= 255.0
if img.ndimension() == 3:
img = img.unsqueeze(0)
# Inference
pred = model(img, augment=False)[0]
# Apply NMS
pred = non_max_suppression(pred,
conf_thres,
iou_thres,
classes=None,
agnostic=False)
# Process detections
for i, det in enumerate(pred): # detections per image
im0 = img0
gn = torch.tensor(im0.shape)[[1, 0, 1, 0]] # normalization gain whwh
if len(det):
# Rescale boxes from img_size to im0 size
det[:, :4] = scale_coords(img.shape[2:], det[:, :4],
im0.shape).round()
# Write results
for *xyxy, conf, cls in reversed(det):
label = f'{names[int(cls)]} {conf:.2f}'
im0 = plot_one_box(xyxy,
im0,
label=label,
color=colors[int(cls)],
line_thickness=3)
return im0
