"""datacollector controller.""" # You may need to import some classes of the controller module. Ex: # from controller import Robot, Motor, DistanceSensor from controller import Supervisor import uuid import numpy as np import os # create the Robot instance. robot = Supervisor() # get the time step of the current world. timestep = int(robot.getBasicTimeStep()) # You should insert a getDevice-like function in order to get the # instance of a device of the robot. Something like: # motor = robot.getDevice('motorname') # ds = robot.getDevice('dsname') # ds.enable(timestep) rf = robot.getDevice("realsenseD405") camera = robot.getDevice("camera") gripper = robot.getDevice("ROBOTIQ 2F-140 Gripper::left finger joint") #= {'left' : robot.getDevice("ROBOTIQ 2F-140 Gripper::left finger joint"), # 'right': robot.getDevice("ROBOTIQ 2F-140 Gripper::right finger joint")} gripper.setPosition(float('inf')) camera.enable(32) camera.recognitionEnable(32) camera.enableRecognitionSegmentation() rf.enable(32) settle_time = 90 elapsed_time = 0 # Randomize all the nodes that start with "random_" rootNode = robot.getRoot() rootChildren = rootNode.getField("children") n = rootChildren.getCount() print(n," nodes") for i in range(n): node = rootChildren.getMFNode(i) if node.getType()==80: # only for solids name=node.getField("name").getSFString() if name.startswith("random"): v=np.random.rand(3) v = v / np.linalg.norm(v) # create unit vector v=[*v,np.random.uniform(-np.pi,+np.pi)] # add random orientation node.getField("rotation").setSFRotation(v) # Create paths if they don't exist path = "../../data/" directories = ['d','rgb','mask','meta'] for directory in directories: directory=path+directory if not os.path.exists(directory): os.makedirs(directory) # Main loop: # - perform simulation steps until Webots is stopping the controller while robot.step(timestep) != -1: gripper.setVelocity(-0.3) # keep gripper open if(elapsed_time>=settle_time): fname = str(uuid.uuid4()) #fname ="" rf.saveImage(path + 'd/'+ fname + "_depth.png",quality=100) camera.saveImage(path + 'rgb/' + fname + "_rgb.png",quality=100) camera.saveRecognitionSegmentationImage(path + 'mask/' + fname + "_mask.png",quality=100) objects=camera.getRecognitionObjects() metadata=[] for object in objects: info = {'id': object.getId(), 'file' : fname, 'position' : np.array(object.getPosition()).tolist(), 'orientation' : np.array(object.getOrientation()).tolist(), 'size' : np.array(object.getSize()).tolist(), 'positionOnImage' : np.array(object.getPositionOnImage()).tolist(), 'sizeOnImage' : np.array(object.getSizeOnImage()).tolist(), 'numberOfColors' : object.getNumberOfColors(), 'colors' : np.ctypeslib.as_array(object.getColors(),(3,)).tolist(), 'model' : object.getModel()} metadata.append(info) print(metadata) import json with open(path + 'meta/' +fname+'_meta.json', 'w') as fp: json.dump(metadata, fp) robot.getSelf().restartController() robot.simulationResetPhysics() robot.simulationReset() # robot.worldReload() elapsed_time+=1 pass # Enter here exit cleanup code.