Label | Explanation | Data Type |
Input Raster | The input image that will be used to detect objects. The input can be a single raster, multiple rasters in a mosaic dataset, an image service, a folder of images, or a feature class with image attachments. | 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. | Feature Class |
Model Definition | 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. | File; String |
Arguments (Optional) | The information from the Model Definition parameter will be used to populate this parameter. These arguments vary, depending on the model architecture. The following are supported model arguments for models trained in ArcGIS. ArcGIS pretrained models and custom deep learning models may have additional arguments that the tool supports.
| Value Table |
Non Maximum Suppression (Optional) | Specifies whether nonmaximum suppression will be performed in which duplicate objects are identified and the duplicate features with lower confidence value are removed.
| Boolean |
Confidence Score Field (Optional) | 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. | String |
Class Value Field (Optional) | 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. | String |
Max Overlap Ratio (Optional) | The maximum overlap ratio for two overlapping features, which is defined as the ratio of intersection area over union area. The default is 0. | Double |
Processing Mode
(Optional) | 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.
| String |
Use pixel space
(Optional) |
Specifies whether inferencing will be performed on images in pixel space.
| Boolean |
Derived Output
Label | Explanation | Data Type |
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. | Raster Dataset |