Brief doc
Convert a strongly typed pcl::PointCloud<pcl::PointT> to a generic variant based PointCloud.
Parameters
format type: ecto::pcl::Format not required default: XYZRGB
Legal Values: XYZ (0) XYZI (1) XYZRGB (2) XYZRGBA (3) XYZRGBNORMAL (4) POINTNORMAL (5) NORMAL (6) PFHSIGNATURE (7) FPFHSIGNATURE (8) VFHSIGNATURE (9)
Format of cloud to grab.
Inputs
input type: boost::shared_ptr<pcl::PointCloud<pcl::PointXYZRGB> const>
An pcl::PointCloud<PointT> type.
Outputs
output type: ecto::pcl::PointCloud
An variant based PointCloud.
Brief doc
Write a cloud to a PCD file
Parameters
binary type: bool not required default: False
Use binary encoding.
filename_format type: std::string not required default: cloud_%04u.pcd
The format string for saving pcds, must succeed with a single unsigned int argument.
Inputs
input type: ecto::pcl::PointCloud
A point cloud to put in a pcd file.
Brief doc
Smooth a cloud with MLS.
Parameters
polynomial_order type: int not required default: 2
The polynomial order to fit.
search_radius type: double not required default: 0.03
Sphere to be considered a neighbor.
Inputs
input type: ecto::pcl::PointCloud
The cloud to filter
Outputs
output type: ecto::pcl::PointCloud
The smoothed cloud.
Brief doc
This cell provides Viewpoint Feature Histogram estimation.
Parameters
k_search type: int not required default: 0
The number of k nearest neighbors to use for feature estimation.
radius_search type: double not required default: 0.0
The sphere radius to use for determining the nearest neighbors used for feature estimation.
spatial_locator type: int not required default: 0
The search method to use: FLANN(0), ORGANIZED(1).
Inputs
input type: ecto::pcl::PointCloud
Input cloud.
normals type: ecto::pcl::FeatureCloud
Normals to use.
Outputs
output type: ecto::pcl::FeatureCloud
Cloud of features.
Brief doc
Segmentation using Sample Consensus from Normals.
Parameters
axis_x type: double not required default: 0.0
X component of desired perpendicular vector for model.
axis_y type: double not required default: 0.0
Y component of desired perpendicular vector for model.
axis_z type: double not required default: 0.0
Z component of desired perpendicular vector for model.
distance_threshold type: double not required default: 0.0
Doistance to model threshold.
eps_angle type: double not required default: 0.0
Angle epsilon (delta) threshold.
max_iterations type: int not required default: 50
Maximum number of iterations before giving up.
method type: int not required default: 0
Type of sample consensus method to use.
model_type type: int not required default: -1
Type of model to use.
normal_distance_weight type: double not required default: 0.1
Relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) betwen point normals and the plane normal.
optimize_coefficients type: bool not required default: True
True if a coefficient refinement is required.
probability type: double not required default: 0.99
Probability of choosing at least one sample free from outliers.
radius_max type: double not required default: 1.79769313486e+308
Maximum allowable radius limits for the model.
radius_min type: double not required default: -1.79769313486e+308
Minimum allowable radius limits for the model.
Inputs
indices type: boost::shared_ptr<pcl::PointIndices const>
Indices of points of interest in input.
input type: ecto::pcl::PointCloud
Input cloud.
normals type: ecto::pcl::FeatureCloud
Normals to use.
Outputs
inliers type: boost::shared_ptr<pcl::PointIndices const>
Inliers of the model.
model type: boost::shared_ptr<pcl::ModelCoefficients const>
Model found during segmentation.
Brief doc
Write a cloud to a PLY file
Parameters
filename_format type: std::string not required default: cloud_%04u.ply
The format string for saving PLY files, must succeed with a single unsigned int argument.
Inputs
input type: ecto::pcl::PointCloud
A point cloud to put in a pcd file.
Brief doc
Remove noisy measurements.
Parameters
min_neighbors type: int not required default: 1
The minimum number of neighbors in the radius.
search_radius type: double not required default: 0.0
The number of points to use for mean distance estimation.
Inputs
input type: ecto::pcl::PointCloud
The cloud to filter
Outputs
output type: ecto::pcl::PointCloud
Filtered Cloud.
Brief doc
Project points of a cloud onto a model that they are inliers of.
Parameters
copy_all_data type: bool not required default: False
Sets whether all data will be returned, or only the projected inliers.
model_type type: int not required default: 0
The type of model to use.
Inputs
input type: ecto::pcl::PointCloud
The cloud to filter
model type: boost::shared_ptr<pcl::ModelCoefficients const>
Model to use for projection.
Outputs
output type: ecto::pcl::PointCloud
Filtered Cloud.
Brief doc
Extract a new cloud given an existing cloud and a set of indices to extract.
Parameters
keep_organized type: bool not required default: False
Sets whether the resultant cloud should remain organized
negative type: bool not required default: False
Sets whether the indices should be returned, or all points _except_ the indices.
Inputs
indices type: boost::shared_ptr<pcl::PointIndices const>
The indices to extract.
input type: ecto::pcl::PointCloud
The cloud to filter
Outputs
output type: ecto::pcl::PointCloud
Filtered Cloud.
Brief doc
Crops and keeps organized a given point cloud.
Parameters
crop_enabled type: bool not required default: True
If the cropper cell is enabled
x_max type: float not required default: 3.40282346639e+38
The maximum x value (in the camera reference frame)
x_min type: float not required default: -3.40282346639e+38
The minimum x value (in the camera reference frame)
y_max type: float not required default: 3.40282346639e+38
The maximum y value (in the camera reference frame)
y_min type: float not required default: -3.40282346639e+38
The minimum y value (in the camera reference frame)
z_max type: float not required default: 3.40282346639e+38
The maximum z value (in the camera reference frame)
z_min type: float not required default: -3.40282346639e+38
The minimum z value (in the camera reference frame)
Inputs
input type: ecto::pcl::PointCloud
The cloud to filter
Outputs
output type: ecto::pcl::PointCloud
The cropped cloud.
Brief doc
Viewer of clouds
Parameters
window_name type: std::string not required default: cloud viewer
The window name
Inputs
input type: ecto::pcl::PointCloud
The cloud to view
Brief doc
This cell provides Fast Point Feature Histogram estimation.
Parameters
k_search type: int not required default: 0
The number of k nearest neighbors to use for feature estimation.
radius_search type: double not required default: 0.0
The sphere radius to use for determining the nearest neighbors used for feature estimation.
spatial_locator type: int not required default: 0
The search method to use: FLANN(0), ORGANIZED(1).
Inputs
input type: ecto::pcl::PointCloud
Input cloud.
normals type: ecto::pcl::FeatureCloud
Normals to use.
Outputs
output type: ecto::pcl::FeatureCloud
Cloud of features.
Brief doc
Normal estimation
Parameters
k_search type: int not required default: 0
The number of k nearest neighbors to use for feature estimation.
radius_search type: double not required default: 0.0
The sphere radius to use for determining the nearest neighbors used for feature estimation.
spatial_locator type: int not required default: 0
The search method to use: FLANN(0), ORGANIZED(1).
vp_x type: double not required default: 0.0
Viewpoint x component.
vp_y type: double not required default: 0.0
Viewpoint y component.
vp_z type: double not required default: 0.0
Viewpoint z component.
Inputs
input type: ecto::pcl::PointCloud
The cloud to filter
Outputs
output type: ecto::pcl::FeatureCloud
Cloud of features.
Brief doc
This cell provides Point Feature Histogram estimation.
Parameters
k_search type: int not required default: 0
The number of k nearest neighbors to use for feature estimation.
radius_search type: double not required default: 0.0
The sphere radius to use for determining the nearest neighbors used for feature estimation.
spatial_locator type: int not required default: 0
The search method to use: FLANN(0), ORGANIZED(1).
Inputs
input type: ecto::pcl::PointCloud
Input cloud.
normals type: ecto::pcl::FeatureCloud
Normals to use.
Outputs
output type: ecto::pcl::FeatureCloud
Cloud of features.
Brief doc
PassThrough filter that returns PointIndices
Parameters
filter_field_name type: std::string not required default:
The name of the field to use for filtering.
filter_limit_max type: double not required default: 3.40282346639e+38
Maximum value for the filter.
filter_limit_min type: double not required default: 1.17549435082e-38
Minimum value for the filter.
filter_limit_negative type: bool not required default: False
To negate the filter limits.
Inputs
indices type: boost::shared_ptr<pcl::PointIndices const>
relevant indices of the input cloud [optional].
input type: ecto::pcl::PointCloud
The cloud to filter
Outputs
output type: boost::shared_ptr<pcl::PointIndices const>
filtered point indices
Brief doc
Uses a set of point indices that respresent a planar model, and together with a given height, generates a 3D polygonal prism.
Parameters
height_max type: double not required default: 1.0
Maximum allowable height limits for the model.
height_min type: double not required default: 0.0
Minimum allowable height limits for the model.
Inputs
input type: ecto::pcl::PointCloud
Input cloud.
planar_hull type: ecto::pcl::PointCloud
Planar hull to use.
Outputs
inliers type: boost::shared_ptr<pcl::PointIndices const>
Inliers of the model.
Brief doc
PassThrough filter
Parameters
filter_field_name type: std::string not required default:
The name of the field to use for filtering.
filter_limit_max type: double not required default: 3.40282346639e+38
Maximum value for the filter.
filter_limit_min type: double not required default: 1.17549435082e-38
Minimum value for the filter.
filter_limit_negative type: bool not required default: False
To negate the limits or not.
Inputs
input type: ecto::pcl::PointCloud
The cloud to filter
Outputs
output type: ecto::pcl::PointCloud
Filtered Cloud.
Brief doc
Read a cloud from a PCD file
Parameters
filename type: std::string not required default:
Name of the pcd file
format type: ecto::pcl::Format not required default: XYZRGB
Legal Values: XYZ (0) XYZI (1) XYZRGB (2) XYZRGBA (3) XYZRGBNORMAL (4) POINTNORMAL (5) NORMAL (6) PFHSIGNATURE (7) FPFHSIGNATURE (8) VFHSIGNATURE (9)
Format of cloud found in PCD file.
Outputs
output type: ecto::pcl::PointCloud
A point cloud from the pcd file.
Brief doc
Read images from a directory.
Inputs
depth_buffer type: boost::shared_ptr<std::vector<unsigned short, std::allocator<unsigned short> > const>
depth_height type: int
Depth frame height.
depth_width type: int
Depth frame width.
image_buffer type: boost::shared_ptr<std::vector<unsigned char, std::allocator<unsigned char> > const>
image_channels type: int
Number of image channels.
image_height type: int
Image frame height.
image_width type: int
Image frame width.
Outputs
output type: ecto::pcl::PointCloud
Brief doc
Remove noisy measurements.
Parameters
mean_k type: int not required default: 1
The number of points to use for mean distance estimation.
negative type: bool not required default: False
Sets whether the indices should be returned, or all points _except_ the indices.
stddev type: double not required default: 0.0
The standard deviation multiplier threshold.
Inputs
input type: ecto::pcl::PointCloud
The cloud to filter
Outputs
output type: ecto::pcl::PointCloud
Filtered Cloud.
Brief doc
Segmentation using Sample Consensus.
Parameters
axis_x type: double not required default: 0.0
X component of desired perpendicular vector for model.
axis_y type: double not required default: 0.0
Y component of desired perpendicular vector for model.
axis_z type: double not required default: 0.0
Z component of desired perpendicular vector for model.
distance_threshold type: double not required default: 0.0
Doistance to model threshold.
eps_angle type: double not required default: 0.0
Angle epsilon (delta) threshold.
max_iterations type: int not required default: 50
Maximum number of iterations before giving up.
method type: int not required default: 0
Type of sample consensus method to use.
model_type type: int not required default: -1
Type of model to use.
optimize_coefficients type: bool not required default: True
True if a coefficient refinement is required.
probability type: double not required default: 0.99
Probability of choosing at least one sample free from outliers.
radius_max type: double not required default: 1.79769313486e+308
Maximum allowable radius limits for the model.
radius_min type: double not required default: -1.79769313486e+308
Minimum allowable radius limits for the model.
Inputs
indices type: boost::shared_ptr<pcl::PointIndices const>
Indices of points of interest in input.
input type: ecto::pcl::PointCloud
The cloud to filter
Outputs
inliers type: boost::shared_ptr<pcl::PointIndices const>
Inliers of the model.
model type: boost::shared_ptr<pcl::ModelCoefficients const>
Model found during segmentation.
Brief doc
Convert a generic variant based PointCloud to a strongly typed pcl::PointCloud<pcl::PointT>.
Parameters
format type: ecto::pcl::Format not required default: XYZRGB
Legal Values: XYZ (0) XYZI (1) XYZRGB (2) XYZRGBA (3) XYZRGBNORMAL (4) POINTNORMAL (5) NORMAL (6) PFHSIGNATURE (7) FPFHSIGNATURE (8) VFHSIGNATURE (9)
Format of cloud to grab.
Inputs
input type: ecto::pcl::PointCloud
An variant based PointCloud.
Outputs
output type: ecto::tendril::none
An pcl::PointCloud<PointT> type.
Brief doc
Using libqhull library.
Parameters
dimensionality type: int not required default: 3
Dimensionality of the data (valid: 2 and 3)
Inputs
indices type: boost::shared_ptr<pcl::PointIndices const>
Indices of points of interest in input.
input type: ecto::pcl::PointCloud
The cloud to filter
Outputs
output type: ecto::pcl::PointCloud
Points that form the the convex hull.
Brief doc
Merges two clouds of the same type.
Inputs
input type: ecto::pcl::PointCloud
Input cloud.
input2 type: ecto::pcl::PointCloud
Second cloud to merge
Outputs
output type: ecto::pcl::PointCloud
Merged cloud.
Brief doc
Voxel grid filter
Parameters
filter_field_name type: std::string not required default:
The name of the field to use for filtering.
filter_limit_max type: double not required default: 3.40282346639e+38
Maximum value for the filter.
filter_limit_min type: double not required default: -3.40282346639e+38
Minimum value for the filter.
filter_limit_negative type: bool not required default: False
To negate the limits or not.
leaf_size type: float not required default: 0.0500000007451
The size of the leaf(meters), smaller means more points...
Inputs
input type: ecto::pcl::PointCloud
The cloud to filter
Outputs
output type: ecto::pcl::PointCloud
Filtered Cloud.
Brief doc
Segmentation for cluster extraction in a Euclidean sense.
Parameters
cluster_tolerance type: double not required default: 0.05
Spatial cluster tolerance as a measure in the L2 Euclidean space.
max_cluster_size type: int not required default: 2147483647
Maximum number of points that a cluster needs to containin order to be considered valid.
min_cluster_size type: int not required default: 1
Minimum number of points that a cluster needs to containin order to be considered valid.
Inputs
indices type: boost::shared_ptr<pcl::PointIndices const>
relevant indices of the input cloud [optional].
input type: ecto::pcl::PointCloud
The cloud to filter
Outputs
output type: std::vector<pcl::PointIndices, std::allocator<pcl::PointIndices> >
Clusters.
Brief doc
Extract a point cloud corresponding to the largest cluster.
Inputs
clusters type: std::vector<pcl::PointIndices, std::allocator<pcl::PointIndices> >
Clusters indices.
input type: ecto::pcl::PointCloud
The cloud to filter
Outputs
output type: ecto::pcl::PointCloud
Filtered Cloud.
Brief doc
Concatenate clusters and colr each cluster differently.
Parameters
max_clusters type: int not required default: 100
Maximum number of clusters to output in the cloud.
saturation type: float not required default: 0.800000011921
HSV Saturation of cloud colors on [0, 1]
value type: float not required default: 1.0
Value (brightness) of cloud colors on [0, 1]
Inputs
clusters type: std::vector<pcl::PointIndices, std::allocator<pcl::PointIndices> >
Indices of clusters.
input type: ecto::pcl::PointCloud
The cloud to filter
Outputs
output type: ecto::pcl::PointCloud
Colorized clusters as a single cloud.