ArcGIS REST API - ArcGIS Services - Query Deep Learning Model Info

URL:https://<rasteranalysistools-url>/QueryDeepLearningModelInfo
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, Install Deep Learning Model, Interpolate Points, List Deep Learning Models, Nibble, Segment, Stream Link, Summarize Raster Within, Train Classifier, Uninstall Deep Learning Model, Watershed
Version Introduced:10.7

Description

Query Deep Learning Model Info

The QueryDeepLearningModelInfo operation is used to extract the deep learning model specific settings from the model package item or model definition file.

Request parameters


Parameter	Details
model (Required)	The portal model package Item Id, portal model package item URL, path of the model definition file (.emd), or a JSON string of the entire model definition. Syntax: JSON object describes the input model. `{"itemId": <portal item id>} {"url": <portal item url>} {"uri": <model definition file path>} }` The model definition file path can be a regular UNC path or a server data store relative path. `{"uri": "/rasterStores/myrasterstorename/myemdfilename.emd"} {"uri": "\\\\servername\\datafolder\\myemdfilename.emd"}`
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>/QueryDeepLearningModelInfo/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>/QueryDeepLearningModelsInfo/jobs/<jobId>/results/outModelInfo

Example usage

Below is a sample request URL to QueryDeepLearningModelInfo.

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

JSON Response example

The response returns the outModelInfo output parameter, which has properties for parameter name, data type, and value. The content of the value is a JSON string that describes the essential settings of the deep learning model.

{
 "paramName": "outModelInfo",
 "dataType": "GPString",
 "value": {
  "modelInfo":  "{"Framework":"TensorFlow",\"ModelType\":\"ImageClassification\",\"ParameterInfo\":[{\"name\":\"raster\",\"dataType\":\"raster\",\"required\":\"1\",\"displayName\":\"Raster\",\"description\":\"Input Raster\"},{\"name\":\"model\",\"dataType\":\"string\",\"required\":\"1\",\"displayName\":\"Input Model Definition (EMD) File\",\"description\":\"Input model definition (EMD) JSON file\"},{\"name\":\"device\",\"dataType\":\"numeric\",\"required\":\"0\",\"displayName\":\"Device ID\",\"description\":\"Device ID\"},{\"name\":\"padding\",\"dataType\":\"numeric\",\"value\":\"0\",\"required\":\"0\",\"displayName\":\"Padding\",\"description\":\"Padding\"}]}"
 }
}