{"_id":"5818fc6fbeb0c20f000d4471","parentDoc":null,"category":{"_id":"573b4f62ef164e2900a2b881","__v":0,"project":"55faeacad0e22017005b8265","version":"55faeacad0e22017005b8268","sync":{"url":"","isSync":false},"reference":false,"createdAt":"2016-05-17T17:05:38.443Z","from_sync":false,"order":9,"slug":"algorithm-guide","title":"Algorithms"},"user":"55fae9d4825d5f19001fa379","__v":0,"version":{"_id":"55faeacad0e22017005b8268","project":"55faeacad0e22017005b8265","__v":36,"createdAt":"2015-09-17T16:31:06.800Z","releaseDate":"2015-09-17T16:31:06.800Z","categories":["55faeacbd0e22017005b8269","55faf550764f50210095078e","55faf5b5626c341700fd9e96","55faf8a7825d5f19001fa386","560052f91503430d007cc88f","560054f73aa0520d00da0b1a","56005aaf6932a00d00ba7c62","56005c273aa0520d00da0b3f","5601ae7681a9670d006d164d","5601ae926811d00d00ceb487","5601aeb064866b1900f4768d","5601aee850ee460d0002224c","5601afa02499c119000faf19","5601afd381a9670d006d1652","561d4c78281aec0d00eb27b6","561d588d8ca8b90d00210219","563a5f934cc3621900ac278c","5665c5763889610d0008a29e","566710a36819320d000c2e93","56ddf6df8a5ae10e008e3926","56e1c96b2506700e00de6e83","56e1ccc4e416450e00b9e48c","56e1ccdfe63f910e00e59870","56e1cd10bc46be0e002af26a","56e1cd21e416450e00b9e48e","56e3139a51857d0e008e77be","573b4f62ef164e2900a2b881","57c9d1335fd8ca0e006308ed","57e2bd9d1e7b7220000d7fa5","57f2b992ac30911900c7c2b6","58adb5c275df0f1b001ed59b","58c81b5c6dc7140f003c3c46","595412446ed4d9001b3e7b37","59e76ce41938310028037295","5a009de510890d001c2aabfe","5a96f89c89442e002041144b"],"is_deprecated":false,"is_hidden":false,"is_beta":false,"is_stable":true,"codename":"v1","version_clean":"1.0.0","version":"1"},"project":"55faeacad0e22017005b8265","updates":[],"next":{"pages":[],"description":""},"createdAt":"2016-11-01T20:34:55.874Z","link_external":false,"link_url":"","githubsync":"","sync_unique":"","hidden":false,"api":{"results":{"codes":[]},"settings":"","auth":"required","params":[],"url":""},"isReference":false,"order":148,"body":"### Imagery Examples\n\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/7aadfa1-envi_roi2class_before_web.jpg\",\n        \"envi_roi2class_before_web.jpg\",\n        566,\n        400,\n        \"#82756b\"\n      ],\n      \"caption\": \"Before: WorldView 2 image after AOP correction\"\n    }\n  ]\n}\n[/block]\n\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/098e8b2-envi_roi2class_after_web.jpg\",\n        \"envi_roi2class_after_web.jpg\",\n        566,\n        400,\n        \"#072032\"\n      ],\n      \"caption\": \"After: WorldView 2 image after ROI Classification\"\n    }\n  ]\n}\n[/block]\n### Quickstart\nThis is a workflow example for basic processing.\n[block:code]\n{\n  \"codes\": [\n    {\n      \"code\": \"# Quickstart Example running the task name.\\n\\n# Initialize the Environment.\\nfrom os.path import join, split\\nfrom gbdxtools import Interface\\ngbdx = Interface()\\n\\ntasks = []\\noutput_location = 'ENVI/ROIToClassification'\\n\\ncat_id = '105001000672E000'\\n\\n# Image Auto ordering task parameters\\norder = gbdx.Task(\\\"Auto_Ordering\\\")\\norder.inputs.cat_id = cat_id\\norder.impersonation_allowed = True\\norder.persist = True\\norder.timeout = 36000\\ntasks += [order]\\n\\n# Image AOP task parameters\\naop = gbdx.Task(\\\"AOP_Strip_Processor\\\")\\naop.inputs.data = order.outputs.s3_location.value\\naop.inputs.bands = 'MS'\\naop.inputs.enable_dra = False\\naop.outputs.data.persist = True\\naop.outputs.data.persist_location = output_location+'/aop'\\naop.timeout = 36000\\ntasks += [aop]\\n\\n# Threshold the image\\nenvi_threshold = gbdx.Task(\\\"ENVI_ImageThresholdToROI\\\")\\nenvi_threshold.inputs.input_raster = aop.outputs.data.value\\nenvi_threshold.inputs.roi_name = '[\\\"Water\\\", \\\"Land\\\"]'\\nenvi_threshold.inputs.roi_color = '[[0,255,0],[0,0,255]]'\\nenvi_threshold.inputs.threshold = '[[138,221,0],[222,306,0]]'\\nenvi_threshold.inputs.output_roi_uri_filename = \\\"roi\\\"\\ntasks += [envi_threshold]\\n\\nenvi_roi2class = gbdx.Task(\\\"ENVI_ROIToClassification\\\")\\nenvi_roi2class.inputs.input_raster = aop.outputs.data.value\\nenvi_roi2class.inputs.input_roi = envi_threshold.outputs.output_roi_uri.value\\ntasks += [envi_roi2class]\\n\\nworkflow = gbdx.Workflow(tasks)\\nworkflow.savedata(\\n    envi_threshold.outputs.output_roi_uri, location=join(output_location, 'roi')\\n)\\nworkflow.savedata(\\n    envi_roi2class.outputs.output_raster_uri, location=join(output_location, 'classification')\\n)\\n\\nworkflow.execute()\",\n      \"language\": \"python\"\n    }\n  ]\n}\n[/block]\n### Inputs\nThe following table lists all ENVI_ROIToClassification inputs.\nMandatory (optional) settings are listed as Required = True (Required = False).\n\n  Name  |  Required  |  Default  |  Valid Values  |  Description  \n--------|:----------:|-----------|----------------|---------------\nfile_types|False|N/A|string|GBDX Option. Comma seperated list of permitted file type extensions. Use this to filter input files -- Value Type: STRING`[*]`\ninput_raster|True|N/A|[See ENVIRASTER input type](https://gbdxdocs.digitalglobe.com/docs/envi-task-engine#section-enviraster)|Specify the input raster to apply ROIs to generate a classification image. -- Value Type: ENVIRASTER\ninput_raster_format|False|N/A|[See ENVIRASTER input type](https://gbdxdocs.digitalglobe.com/docs/envi-task-engine#section-enviraster)|Provide the format of the image, for example: landsat-8. -- Value Type: STRING\ninput_raster_band_grouping|False|N/A|[See ENVIRASTER input type](https://gbdxdocs.digitalglobe.com/docs/envi-task-engine#section-enviraster)|Provide the name of the band grouping to be used in the task, ie - panchromatic. -- Value Type: STRING\ninput_raster_filename|False|N/A|[See ENVIRASTER input type](https://gbdxdocs.digitalglobe.com/docs/envi-task-engine#section-enviraster)|Provide the explicit relative raster filename that ENVI will open. This overrides any file lookup in the task runner. -- Value Type: STRING\ninput_roi|True|N/A|[See ENVIROIARRAY input type](https://gbdxdocs.digitalglobe.com/docs/envi-task-engine#section-enviroi)|Specify an ROI or array of ROIs used to create the classification image. -- Value Type: ENVIROIARRAY\noutput_raster_uri_filename|False|N/A|string|Specify a string with the fully-qualified path and filename for OUTPUT_RASTER. -- Value Type: STRING\n\n\n### Outputs\n\nThe following table lists all ENVI_ROIToClassification outputs.\nMandatory (optional) settings are listed as Required = True (Required = False).\n\n  Name  |  Required  |  Default  |  Valid Values  |  Description\n--------|:----------:|-----------|----------------|---------------\ntask_meta_data|False|N/A|directory|GBDX Option. Output location for task meta data such as execution log and output JSON\noutput_raster_uri|True|N/A|directory|Output for OUTPUT_RASTER. -- Value Type: ENVIURI\n\n**Output structure**\n\nThe output_raster_uri file will be written to the specified S3 Customer Account Location.\n\n### Background\nFor additional background information on this task please refer to the [Harris Geospatial ENVI documentation](http://www.harrisgeospatial.com/docs/home.html) and \n[ENVI® ROI To Classification](http://www.harrisgeospatial.com/docs/enviroitoclassificationtask.html). \n\n### Contact\nIf you have any questions or issues with this task, please contact [gbdx-support:::at:::digitalglobe.com](mailto:gbdx-support@digitalglobe.com).","excerpt":"This task creates a classification image from regions of interest (ROIs).  The input ROI file must be created using the [ENVI Image Threshold To ROI Task](http://gbdxdocs.digitalglobe.com/docs/envi-image-threshold-to-roi).  You may use a pre-existing ROI dataset or  produce the final classification as part of a larger workflow. \n\n**GBDX Registered Name:** ENVI_ROIToClassification\n**Provider:** Harris\tGeospatial Solutions","slug":"envi-roi-to-classification","type":"basic","title":"ENVI® ROI to Classification"}

ENVI® ROI to Classification

This task creates a classification image from regions of interest (ROIs). The input ROI file must be created using the [ENVI Image Threshold To ROI Task](http://gbdxdocs.digitalglobe.com/docs/envi-image-threshold-to-roi). You may use a pre-existing ROI dataset or produce the final classification as part of a larger workflow. **GBDX Registered Name:** ENVI_ROIToClassification **Provider:** Harris Geospatial Solutions

### Imagery Examples [block:image] { "images": [ { "image": [ "https://files.readme.io/7aadfa1-envi_roi2class_before_web.jpg", "envi_roi2class_before_web.jpg", 566, 400, "#82756b" ], "caption": "Before: WorldView 2 image after AOP correction" } ] } [/block] [block:image] { "images": [ { "image": [ "https://files.readme.io/098e8b2-envi_roi2class_after_web.jpg", "envi_roi2class_after_web.jpg", 566, 400, "#072032" ], "caption": "After: WorldView 2 image after ROI Classification" } ] } [/block] ### Quickstart This is a workflow example for basic processing. [block:code] { "codes": [ { "code": "# Quickstart Example running the task name.\n\n# Initialize the Environment.\nfrom os.path import join, split\nfrom gbdxtools import Interface\ngbdx = Interface()\n\ntasks = []\noutput_location = 'ENVI/ROIToClassification'\n\ncat_id = '105001000672E000'\n\n# Image Auto ordering task parameters\norder = gbdx.Task(\"Auto_Ordering\")\norder.inputs.cat_id = cat_id\norder.impersonation_allowed = True\norder.persist = True\norder.timeout = 36000\ntasks += [order]\n\n# Image AOP task parameters\naop = gbdx.Task(\"AOP_Strip_Processor\")\naop.inputs.data = order.outputs.s3_location.value\naop.inputs.bands = 'MS'\naop.inputs.enable_dra = False\naop.outputs.data.persist = True\naop.outputs.data.persist_location = output_location+'/aop'\naop.timeout = 36000\ntasks += [aop]\n\n# Threshold the image\nenvi_threshold = gbdx.Task(\"ENVI_ImageThresholdToROI\")\nenvi_threshold.inputs.input_raster = aop.outputs.data.value\nenvi_threshold.inputs.roi_name = '[\"Water\", \"Land\"]'\nenvi_threshold.inputs.roi_color = '[[0,255,0],[0,0,255]]'\nenvi_threshold.inputs.threshold = '[[138,221,0],[222,306,0]]'\nenvi_threshold.inputs.output_roi_uri_filename = \"roi\"\ntasks += [envi_threshold]\n\nenvi_roi2class = gbdx.Task(\"ENVI_ROIToClassification\")\nenvi_roi2class.inputs.input_raster = aop.outputs.data.value\nenvi_roi2class.inputs.input_roi = envi_threshold.outputs.output_roi_uri.value\ntasks += [envi_roi2class]\n\nworkflow = gbdx.Workflow(tasks)\nworkflow.savedata(\n envi_threshold.outputs.output_roi_uri, location=join(output_location, 'roi')\n)\nworkflow.savedata(\n envi_roi2class.outputs.output_raster_uri, location=join(output_location, 'classification')\n)\n\nworkflow.execute()", "language": "python" } ] } [/block] ### Inputs The following table lists all ENVI_ROIToClassification inputs. Mandatory (optional) settings are listed as Required = True (Required = False). Name | Required | Default | Valid Values | Description --------|:----------:|-----------|----------------|--------------- file_types|False|N/A|string|GBDX Option. Comma seperated list of permitted file type extensions. Use this to filter input files -- Value Type: STRING`[*]` input_raster|True|N/A|[See ENVIRASTER input type](https://gbdxdocs.digitalglobe.com/docs/envi-task-engine#section-enviraster)|Specify the input raster to apply ROIs to generate a classification image. -- Value Type: ENVIRASTER input_raster_format|False|N/A|[See ENVIRASTER input type](https://gbdxdocs.digitalglobe.com/docs/envi-task-engine#section-enviraster)|Provide the format of the image, for example: landsat-8. -- Value Type: STRING input_raster_band_grouping|False|N/A|[See ENVIRASTER input type](https://gbdxdocs.digitalglobe.com/docs/envi-task-engine#section-enviraster)|Provide the name of the band grouping to be used in the task, ie - panchromatic. -- Value Type: STRING input_raster_filename|False|N/A|[See ENVIRASTER input type](https://gbdxdocs.digitalglobe.com/docs/envi-task-engine#section-enviraster)|Provide the explicit relative raster filename that ENVI will open. This overrides any file lookup in the task runner. -- Value Type: STRING input_roi|True|N/A|[See ENVIROIARRAY input type](https://gbdxdocs.digitalglobe.com/docs/envi-task-engine#section-enviroi)|Specify an ROI or array of ROIs used to create the classification image. -- Value Type: ENVIROIARRAY output_raster_uri_filename|False|N/A|string|Specify a string with the fully-qualified path and filename for OUTPUT_RASTER. -- Value Type: STRING ### Outputs The following table lists all ENVI_ROIToClassification outputs. Mandatory (optional) settings are listed as Required = True (Required = False). Name | Required | Default | Valid Values | Description --------|:----------:|-----------|----------------|--------------- task_meta_data|False|N/A|directory|GBDX Option. Output location for task meta data such as execution log and output JSON output_raster_uri|True|N/A|directory|Output for OUTPUT_RASTER. -- Value Type: ENVIURI **Output structure** The output_raster_uri file will be written to the specified S3 Customer Account Location. ### Background For additional background information on this task please refer to the [Harris Geospatial ENVI documentation](http://www.harrisgeospatial.com/docs/home.html) and [ENVI® ROI To Classification](http://www.harrisgeospatial.com/docs/enviroitoclassificationtask.html). ### Contact If you have any questions or issues with this task, please contact [gbdx-support@digitalglobe.com](mailto:gbdx-support@digitalglobe.com).