The input image used to detect objects. The input can be a single raster or multiple rasters in a mosaic dataset, image service, or folder of images. A feature class with image attachments is also supported.
|Raster Dataset; Raster Layer; Mosaic Layer; Image Service; Map Server; Map Server Layer; Internet Tiled Layer; Folder; Feature Layer; Feature Class|
Output Detected Objects
The output feature class that will contain geometries circling the object or objects detected in the input image.
This parameter can be an Esri model definition JSON file (.emd), a JSON string, or a deep learning model package (.dlpk). A JSON string is useful when this tool is used on the server so you can paste the JSON string rather than upload the .emd file. The .dlpk file must be stored locally.
It contains the path to the deep learning binary model file, the path to the Python raster function to be used, and other parameters such as preferred tile size or padding.
The function arguments defined in the Python raster function class. This is where additional deep learning parameters and arguments for experiments and refinement are listed, such as a confidence threshold for adjusting the sensitivity. The names of the arguments are populated from the Python module.
Non Maximum Suppression
Specifies whether nonmaximum suppression will be performed in which duplicate objects are identified and the duplicate features with lower confidence value are removed.
Confidence Score Field
The name of the field in the feature class that will contain the confidence scores as output by the object detection method.
This parameter is required when the Non Maximum Suppression parameter is checked.
Class Value Field
The name of the class value field in the input feature class.
If a field name is not specified, a Classvalue or Value field will be used. If these fields do not exist, all records will be identified as belonging to one class.
Max Overlap Ratio
The maximum overlap ratio for two overlapping features, which is defined as the ratio of intersection area over union area. The default is 0.
Specifies how all raster items in a mosaic dataset or an image service will be processed. This parameter is applied when the input raster is a mosaic dataset or an image service.
|Output Classified Raster|
The output classified raster for pixel classification. The name of the raster dataset will be the same as the Output Detected Objects parameter value.
This parameter is only applicable when the model type is Panoptic Segmentation.