Install Deep Learning Model

• URL:https://<rasteranalysistools-url>/InstallDeepLearningModel
  
• Related Resources:Add Image, Calculate Density, Calculate Distance, Calculate Travel Cost,Classify, Classify Pixels Using Deep Learning, Convert Feature to Raster, Convert Raster Function Template, Convert Raster to Feature, Copy Raster, Create Image Collection, Create Viewshed, Delete Image, Delete Image Collection, Detect Objects Using Deep Learning, Determine Optimum Travel Cost Network, Determine Travel Cost Paths to Destinations, Determine Travel Cost Path as Polyline, Export Training Data for Deep Learning, Fill, Flow Accumulation, Flow Direction, Flow Distance, Generate Raster, Interpolate Points, List Deep Learning Model Info, Nibble, Query Deep Learning Model Info, Segment, Stream Link, Summarize Raster Within, Train Classifier, Uninstall Deep Learning Model, Watershed
• Version Introduced:10.7

Description

The InstallDeepLearningModel operation is used to install the uploaded deep learning model package (.dlpk) from portal to the raster analysis image server. The upload model package will be unpacked and saved to the server configuration store.

Request parameters

Parameter	Details
modelPackage (Required)	The portal item Id or URL of a deep learning model package. Syntax: JSON object describes the input model package. {"itemId": <portal item id>} {"url": <portal item url>}
f	The response format. The default response format is html. Values: html | json

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 the jobId to periodically check the status of the job and messages as described in Checking job status. Once the job has successfully completed, you use the jobId to retrieve the results. To track the status, you can make a request of the following form:

https://<raster analysis tools url>/InstallDeepLearningModel/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>/InstallDeepLearningModel/jobs/<jobId>/installSucceed

Example usage

Below is a sample request URL for InstallDeepLearningModel.

https://services.myserver.com/arcgis/rest/services/System/RasterAnalysisTools/GPServer/InstallDeepLearningModel/submitJob

JSON Response example

The response returns the installSucceed parameter, which has properties for parameter name, data type, and value. The content of the value is the installed model location at the image server configuration store.

{
   "paramName": "installSucceed",
   "dataType": "GPString",
   "value": "[resources]models\\raster\\f0e602cf29dd4674ad814773ed361fb6\\tensorflow_objectdetectionapi_tree.emd"
}