- URL:https://<rasteranalysis-url>/ExportTrainingDataforDeepLearning
- Version Introduced:10.7
Description
The ExportTrainingDataforDeepLearning service generates training sample image chips from the input imagery data with labeled vector data or classified images. The output of this service tool is the data store string where the output image chips, labels, and metadata files will be stored.
Request parameters
Parameter | Details |
---|---|
inputRaster (Required) | The image that will be classified. This can be specified as the portal item ID, image service URL, cloud raster dataset, shared raster dataset, a feature service with image attachments, or a raster dataset or image collection in the data store. At least one type of input must be provided in the JSON object. If multiple inputs are provided, itemId takes priority. Syntax: JSON object describes the inputRaster. Example:
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outputLocation (Required) | The output location for training sample data. This can be specified as the output folder name, a file share raster data store path, a file share data store path, or a shared file system path. Example:
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inputClassData (Required) | The labeled data, either in a feature service or an image service. Vector inputs should follow a training sample format as generated by the ArcGIS Pro Training Sample Manager; raster inputs should follow a classified raster format as generated by the Classify Raster tool. Syntax: JSON object describes the inputClassData. Example:
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chipFormat | Specifies the raster format that will be used for the image chip outputs. Values: TIFF | PNG | JPEG | MRF (Meta Raster Format) Example:
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tileSize | The size of the image chips. This is specified as a name value pair for x and y dimension values. Syntax: A JSON object describes the tileSize. Example:
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strideSize | The distance to move in the x and y directions when creating the next image chip. This is specified as a name value pair for x and y dimension values. When stride is equal to the tile size, there will be no overlap. When stride is equal to half the tile size, there will be 50 percent overlap. Syntax: A JSON object describes the strideSize. Example:
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metadataFormat | Specifies the format of the output metadata labels. If the input training sample data is a feature class layer, such as a building layer or standard classification training sample file, use the KITTI_rectangles or PASCAL_VOC_rectangles option. The output metadata is a .txt file or .xml file containing the training sample data contained in the minimum bounding rectangle. The name of the metadata file matches the input source image name. If the input training sample data is a class map, use the Classified_Tiles option as the output metadata format. Options:
PASCAL_VOC_rectangles example
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classValueField | The field that contains the class values. If no field is specified, the system searches for a value or classvalue field. If the feature does not contain a class field, it is assumed that all records belong to one class. Example:
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bufferRadius | The radius for a buffer around each training sample to delineate a training sample area. This allows you to create circular polygon training samples from points. Example:
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inputMaskPolygons | A polygon feature class that delineates the area where image chips will be created. Only image chips that fall completely within the polygons will be created. Example:
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rotationAngle | The rotation angle that will be used to generate additional image chips. An image chip will be generated with a rotation angle of 0, which means no rotation. It will then be rotated at the specified angle to create an additional image chip. The same training samples will be captured at multiple angles in multiple image chips for data augmentation. The default rotation angle is 0. Example:
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referenceSystem | Specifies the type of reference system to be used to export the image tiles, either MAP_SPACE or PIXEL_SPACE. Choose MAP_SPACE when the input image is in the map-based coordinate system. This is the default value. Use PIXEL_SPACE when the input image is in image space with no rotation and no distortion. Values: MAP_SPACE | PIXEL_SPACE |
processAllRasterItems | Specifies how raster items in an image service will be processed. When false, all raster items in the image service will be mosaicked together and processed. This is the default option. When true, all raster items in the image service will be processed as a separate image. Values: true | false |
blackenAroundFeature | Specifies whether the pixels around each object or feature in each image tile will be darkened. This parameter applies only when the metadata format is set to Labeled_Tiles and an input feature class or classified raster has been specified. When false, pixels surrounding objects or features will not be darkened. This is the default. When true, pixels surrounding objects or features will be darkened. Values: true | false |
fixChipSize | Specifies whether the exported tiles will be cropped so that they are all the same size. This parameter applies only when the metadata format is set to Labeled_Tiles and an input feature class or classified raster has been specified. When true, exported tiles will be the same size and will center on the feature. This is the default. When false, exported tiles will be cropped so that the bounding geometry surrounds only the feature in the image tile. Values: true | false |
additionalInputRaster(Optional | An additional input imagery source that will be used for image translation methods. This parameter is valid when the metadataFormat parameter is set to Classified_Tiles, Export_Tiles, or CycleGAN. The value should be the portal item ID, image service URL, cloud raster dataset, or shared raster dataset that will be classified.. At least one type of input must be provided in the JSON object. If multiple inputs are provided, the itemId takes priority. Syntax: JSON object describes the additionalinputRaster. Example:
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inputInstanceData(Optional) | The training sample data collected that contains classes for instance segmentation. The input can also be a point feature class without a class value field or an integer raster without any class information. This parameter is only valid when the metadataFormat parameter is set to Panoptic_Segmentation . Example:
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instanceClassValueField(Optional) | The minimum overlap percentage for a feature to be included in the training data. If the percentage overlap is less than the value specified, the feature will be excluded from the training chip and will not be added to the label file. The percent value is expressed as a decimal. For example, to specify an overlap of 20 percent, use a value of 0.2. The default value is 0, which means that all features will be included. This parameter improves performance of the tool and also improves inferencing. The speed is improved because fewer training chips are created. Inferencing is improved because the model is trained to only detect large patches of objects and ignores small corners of features. This parameter is only honored when the inputClassData parameter value is a feature service. Example:
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context | Contains settings that affect task processing. This parameter has the following settings:
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f | The response format. The default response format is html. Values: html | json | pjson |
Additional KITTI metadata format information
The table below describes the 15 values in the KITTI metadata format. Only 5 of the possible 15 values are used in the tool: the class name (in column 1) and the minimum bounding rectangle composed of four image coordinate locations (columns 5–8). The minimum bounding rectangle encompasses the training chip used in the deep learning classifier.
Column | Name | Description |
---|---|---|
1 | Class value | The class value of the object listed in the stats.txt file. |
2–4 | Unused | |
5–8 | Bbox | The two-dimensional bounding box of objects in the image, based on a 0-based image space coordinate index. The bounding box contains the four coordinates for the left, top, right, and bottom pixels. |
9–15 | Unused |
Example usage
The following is a sample GET request URL for ExportTrainingDataforDeepLearning:
https://machine.domain.com/webadaptor/rest/services/System/RasterAnalysisTools/GPServer/ExportTrainingDataforDeepLearning?inputRaster={"itemId":89964029c5354407a4f817187144be42}&outputLocation=/rasterStores/myrasterstore/rooftoptrainingsamples&inputClassData={"itemId":66b1f5fa24b14217a1129f8ab688386a}&chipFormat=TIFFtileSize={"x":256,"y":256}&strideSize={"x":128,"y":128}&metadataFormat=KITTI_rectangles&classValueField=&bufferRadius=1&inputMaskPolygons=&rotationAngle=0&referenceSystem=MAP_SPACE&processAllRasterItems=false&blackenAroundFeature=false&fixChipSize=true&f=pjson
The following is a sample POST request URL for ExportTrainingDataforDeepLearning:
POST /webadaptor/rest/services/System/RasterAnalysisTools/GPServer/ExportTrainingforDeepLearning HTTP/1.1
HOST: machine.domain.com
Content-Type: application/x-www-form-urlencoded
Content-Length: []
inputRaster={"itemId":89964029c5354407a4f817187144be42}&outputLocation=/rasterStores/myrasterstore/rooftoptrainingsamples&inputClassData={"itemId":66b1f5fa24b14217a1129f8ab688386a}&chipFormat=TIFFtileSize={"x":256,"y":256}&strideSize={"x":128,"y":128}&metadataFormat=KITTI_rectangles&classValueField=&bufferRadius=1&inputMaskPolygons=&rotationAngle=0&referenceSystem=MAP_SPACE&processAllRasterItems=false&blackenAroundFeature=false&fixChipSize=true&f=pjson
Response
When you submit a request, the task assigns a unique job ID for the transaction.
Syntax:{
"jobId": "<unique job identifier>",
"jobStatus": "<job status>"
}
After the initial request is submitted, you can use jobId to periodically review the status of the job and messages as described in Checking job status. Once the job has successfully completed, use jobId to retrieve the results. To track the status, you can make a request of the following form:
https://<raster analysis tools url>/ExportTrainingDataforDeepLearning/jobs/<jobId>
When the status of the job request is esriJobSucceeded, you can access the results of the analysis by making a request of the following form:
https://<raster analysis tools url>/ExportTrainingDataforDeepLearning/jobs/<jobId>/results/outLocation
JSON Response example
The response returns the outLocation parameter, which provides the output location of the training data and has properties for parameter name, data type, and value. The content of the value is always the output data store item's itemId value or URL.
{
"paramName": "outLocation",
"dataType": "GPString",
"value": {
"uri": "/rasterStores/myrasterstore/rooftops"
}
}