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controllers/datacollector/datacollector.py

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+"""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.

datasetbuilder.py

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+from os import listdir
+from datasets import Dataset, Image
+import json
+import huggingface_hub
+
+huggingface_hub.login('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')
+
+all_rgb=listdir('data/rgb') 
+all_rgb=['data/rgb/' + f for f in all_rgb]
+
+all_d=listdir('data/d')
+all_d=['data/d/' + f for f in all_d]
+
+all_mask=listdir('data/mask')
+all_mask=['data/mask/' + f for f in all_mask]
+
+
+all_json =listdir('data/meta')
+all_jsons=[]
+
+for jsonfilename in all_json:
+    with open('data/meta/'+jsonfilename) as json_file:
+        data = json.load(json_file)
+        all_jsons.append(data)
+
+
+ds=Dataset.from_dict({'rgb' : all_rgb, 
+                      'depth' : all_d, 
+                      'mask' : all_mask,
+                      'meta' : all_jsons}
+                      ).cast_column('rgb',Image()).cast_column('depth',Image()).cast_column('mask',Image())
+
+ds.push_to_hub('correll/semanticsegmentationandposeestimationfromrgbd')

worlds/.webots_grasp.wbproj

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+Webots Project File version R2023b
+perspectives: 000000ff00000000fd0000000200000001000003520000030bfc0200000001fb0000001400540065007800740045006400690074006f007201000000000000030b0000008a00ffffff0000000300000700000000d9fc0100000001fb0000001a0043006f006e0073006f006c00650041006c006c0041006c006c0100000000000007000000008700ffffff000003ac0000030b00000001000000020000000100000008fc00000000
+simulationViewPerspectives: 000000ff00000001000000020000016c000001950100000002010000000101
+sceneTreePerspectives: 000000ff00000001000000030000001e000000c0000000fa0100000002010000000201
+maximizedDockId: -1
+centralWidgetVisible: 1
+orthographicViewHeight: 1
+textFiles: 0 "controllers/datacollector/datacollector.py"
+consoles: Console:All:All
+renderingDevicePerspectives: UR5e:camera;1;0.210701;0.517958;0.360222
+renderingDevicePerspectives: UR5e:realsenseD405;1;0.22713;0.490023;0.036161