Namespaces |
| namespace | run_segmentation_PR2 |
Functions |
| def | run_segmentation_PR2.create_default_scan_dataset |
| def | run_segmentation_PR2.define_ROI_polygons |
| | MAKE SURE THAT THESE MATCH ORIGINAL TAKE: CROP CAMERA IMAGE TO RIO.
|
| def | run_segmentation_PR2.show_image |
Variables |
| tuple | run_segmentation_PR2.ac = acquire_pr2_data.AcquireCloud() |
| | run_segmentation_PR2.CalibrationVisual = True |
| tuple | run_segmentation_PR2.cfg = configuration.configuration(DATA_LOCATION, ROBOT) |
| | CHANGE THIS TO THE DIRECTORY WITH RESULTS FROM CODY: change 'codyRobot' to 'dummyScanner' or code tries to find camera drivers, etc.
|
| | run_segmentation_PR2.colors = pc.map_polys |
| tuple | run_segmentation_PR2.crop_region = (0.3,0.3,0.3,0.3) |
| tuple | run_segmentation_PR2.data = np.asarray(pc.pts3d_bound) |
| tuple | run_segmentation_PR2.data_idx = np.where(np.asarray(pc.map_polys) == processor.LABEL_SURFACE) |
| tuple | run_segmentation_PR2.DATA_LOCATION = roslib.packages.get_pkg_dir('clutter_segmentation') |
| string | run_segmentation_PR2.DATASET_ID = 'pr2_example_0003' |
| | run_segmentation_PR2.displayOn = True |
| tuple | run_segmentation_PR2.feature_data = pc.generate_features(NUMBER_OF_POINTS,False, True) |
| string | run_segmentation_PR2.filename = 'data/' |
| | run_segmentation_PR2.h = image_size.height |
| tuple | run_segmentation_PR2.image_size = cv.cvGetSize(pc.img) |
| | pc.map = (pc.camPts_bound, pc.camPts, pc.idx_list, pc.pts3d_bound,pc.scan_indices_bound, pc.intensities_bound)
|
| | run_segmentation_PR2.IS_LABELED = True |
| string | run_segmentation_PR2.MODE = 'all_post' |
| tuple | run_segmentation_PR2.N = len(idx_list) |
| tuple | run_segmentation_PR2.Nbound = len( idx_list[idx_list] ) |
| int | run_segmentation_PR2.NUMBER_OF_POINTS = 2000 |
| float | run_segmentation_PR2.object_height = 0.1 |
| | Placement routine.
|
| tuple | run_segmentation_PR2.overlay_img = pc.draw_mapped_laser_into_image(None, pc.pts3d, pc.img) |
| tuple | run_segmentation_PR2.pc = processor.processor(cfg) |
| tuple | run_segmentation_PR2.pl = Placement(pc, resolution) |
| | object_height = 0.1
|
| tuple | run_segmentation_PR2.placement_point = pl.test_placement(polygon, object_height) |
| | REPLACE WITH MY OWN CLASS DEFINITION WITH FUNCTIONs.
|
| tuple | run_segmentation_PR2.polygon = label_object() |
| tuple | run_segmentation_PR2.polygon_labels = list(1 for x in range(m)) |
| | pc.display_3d('labels')###
|
| tuple | run_segmentation_PR2.pub = rospy.Publisher('labeled_cloud', PointCloud) |
| list | run_segmentation_PR2.resolution = [.01*SCALE, .01*SCALE] |
| string | run_segmentation_PR2.ROBOT = 'PR2' |
| | run_segmentation_PR2.SAVE_INTENSITY_IMAGE = False |
| | run_segmentation_PR2.SAVE_UNUSED_NEIGHBORS_TO = False |
| | pc.display_all_data()###
|
| int | run_segmentation_PR2.SCALE = 1 |
| | run_segmentation_PR2.SHOW_IN_ROS = True |
| | previously 1000, False,True
|
| tuple | run_segmentation_PR2.table_height = np.mean(data, axis=1) |
| | run_segmentation_PR2.USE_POLYGONS = True |
| | run_segmentation_PR2.w = image_size.width |
| int | run_segmentation_PR2.z_above_floor = 0 |