nonMaximumSuppression

a configuration value, determining the intersection-over-union threshold when the non-maximum suppression is run.

the input tensor holding the scores for each bounding box. The tensor must be a multi-dimensional tensor of with dimensions = Nx1 or 1xN, where N is the number of input bounding boxes. The data type must be one of DataType.FLOAT64, DataType.FLOAT32, DataType.Image.R_FLOAT, or DataType.Image.R_DOUBLE.

the input tensor holding the box boundaries. The boundaries are expected to be expressed in XXYY format. The tensor must be a multi-dimensional tensor of datatype being one of DataType.FLOAT64 or DataType.FLOAT32, with dimensions = Nx4, where N is the number of input bounding boxes and must match that of scores. Alternatively, the tensor can also be a multi-dimensional image tensor with dimensions = Nx1 or 1xN, of a floating-point pixel type with 4 channels (R, G, B and A channels of one pixel will be treated as the Xmin, Xmax, Ymin, Ymax of a bounding box).

an optional result, holding first M scores of bounding boxes passed NMS, sorted from highest to lowest. The tensor, if provided, must be a multi-dimensional tensor of with dimensions = Mx1 or 1xM. The data type must be one of DataType.FLOAT64, DataType.Image.R_FLOAT, DataType.Image.R_FLOAT_DYNAMIC, DataType.Image.R_DOUBLE.

an optional result, holding first M bounding boxes passed NMS, sorted from the highest score to the lowest, matching the scores output from scoresResult. The tensor, if provided, must be a multi-dimensional tensor of datatype being one of DataType.FLOAT64 or DataType.FLOAT32, with dimensions = Mx4, where M is the number of input bounding boxes and must match that of scores. Alternatively, the tensor can also be a multi-dimensional image tensor with dimensions = Mx1 or 1xM, of a floating-point pixel type with 4 channels (R, G, B and A channels of one pixel will store the Xmin, Xmax, Ymin and Ymax of a bounding box).

an optional result, holding the original indices in the boxes input of the first M bounding boxes passed NMS, sorted by the bounding boxes' scores, from the highest to the lowest, matching the scores and boxes output from scoresResult and boxesResult. The tensor, if provided, must be a multi-dimensional tensor of a non-pixel datatype or a RED-channel-only pixel type, with dimensions = Mx1, or 1xM. The data type must be one of the integral types.

If the usage is not allowed by the SpatialML run-time Framework, or if the framework encounters internal error and cannot perform the requested behavior.