<Microsoft Cognitive Services> developer portal

Custom_Vision_Training_3.1

TrainProject

Queues project for training.

Select the testing console in the region where you created your resource:

Request URL

https://{endpoint}/customvision/v3.1/training/projects/{projectId}/train[?trainingType][&reservedBudgetInHours][&forceTrain][&notificationEmailAddress]

Request parameters

projectId

string

Format - uuid. The project id.

trainingType (optional)

string

The type of training to use to train the project (default: Regular).

reservedBudgetInHours (optional)

integer

Format - int32. The number of hours reserved as budget for training (if applicable).

forceTrain (optional)

boolean

Whether to force train even if dataset and configuration does not change (default: false).

notificationEmailAddress (optional)

string

The email address to send notification to when training finishes (default: null).

Request headers

Training-Key

string

API key.

Training-key

string

Subscription key which provides access to this API. Found in your Profile.

Request body

{
  "id": "string",
  "name": "string",
  "status": "string",
  "created": "string",
  "lastModified": "string",
  "trainedAt": "string",
  "projectId": "string",
  "exportable": true,
  "exportableTo": [
    "CoreML"
  ],
  "domainId": "string",
  "classificationType": "Multiclass",
  "trainingType": "Regular",
  "reservedBudgetInHours": 0,
  "trainingTimeInMinutes": 0,
  "publishName": "string",
  "originalPublishResourceId": "string"
}

{
  "description": "Iteration model to be sent over JSON.",
  "required": [
    "name"
  ],
  "type": "object",
  "properties": {
    "id": {
      "format": "uuid",
      "description": "Gets the id of the iteration.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "name": {
      "description": "Gets or sets the name of the iteration.",
      "type": "string",
      "readOnly": false,
      "x-nullable": false
    },
    "status": {
      "description": "Gets the current iteration status.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "created": {
      "format": "date-time",
      "description": "Gets the time this iteration was completed.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "lastModified": {
      "format": "date-time",
      "description": "Gets the time this iteration was last modified.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "trainedAt": {
      "format": "date-time",
      "description": "Gets the time this iteration was last modified.",
      "type": "string",
      "readOnly": true,
      "x-nullable": true
    },
    "projectId": {
      "format": "uuid",
      "description": "Gets the project id of the iteration.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "exportable": {
      "description": "Whether the iteration can be exported to another format for download.",
      "type": "boolean",
      "readOnly": true,
      "x-nullable": false
    },
    "exportableTo": {
      "description": "A set of platforms this iteration can export to.",
      "type": "array",
      "items": {
        "enum": [
          "CoreML",
          "TensorFlow",
          "DockerFile",
          "ONNX",
          "VAIDK"
        ],
        "type": "string",
        "x-nullable": false
      },
      "readOnly": true
    },
    "domainId": {
      "format": "uuid",
      "description": "Get or sets a guid of the domain the iteration has been trained on.",
      "type": "string",
      "readOnly": true,
      "x-nullable": true
    },
    "classificationType": {
      "description": "Gets the classification type of the project.",
      "enum": [
        "Multiclass",
        "Multilabel"
      ],
      "type": "string",
      "readOnly": true,
      "x-nullable": true,
      "x-ms-enum": {
        "name": "Classifier",
        "modelAsString": true
      }
    },
    "trainingType": {
      "description": "Gets the training type of the iteration.",
      "enum": [
        "Regular",
        "Advanced"
      ],
      "type": "string",
      "readOnly": true,
      "x-nullable": false,
      "x-ms-enum": {
        "name": "TrainingType",
        "modelAsString": true
      }
    },
    "reservedBudgetInHours": {
      "format": "int32",
      "description": "Gets the reserved advanced training budget for the iteration.",
      "type": "integer",
      "readOnly": true,
      "x-nullable": false
    },
    "trainingTimeInMinutes": {
      "format": "int32",
      "description": "Gets the training time for the iteration.",
      "type": "integer",
      "readOnly": true,
      "x-nullable": false
    },
    "publishName": {
      "description": "Name of the published model.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "originalPublishResourceId": {
      "description": "Resource Provider Id this iteration was originally published to.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    }
  }
}

Sample
Schema

<Iteration>
  <id>string</id>
  <name>string</name>
  <status>string</status>
  <created>string</created>
  <lastModified>string</lastModified>
  <trainedAt>string</trainedAt>
  <projectId>string</projectId>
  <exportable>true</exportable>
  <exportableTo>CoreML</exportableTo>
  <domainId>string</domainId>
  <classificationType>Multiclass</classificationType>
  <trainingType>Regular</trainingType>
  <reservedBudgetInHours>0</reservedBudgetInHours>
  <trainingTimeInMinutes>0</trainingTimeInMinutes>
  <publishName>string</publishName>
  <originalPublishResourceId>string</originalPublishResourceId>
</Iteration>

{
  "description": "Iteration model to be sent over JSON.",
  "required": [
    "name"
  ],
  "type": "object",
  "properties": {
    "id": {
      "format": "uuid",
      "description": "Gets the id of the iteration.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "name": {
      "description": "Gets or sets the name of the iteration.",
      "type": "string",
      "readOnly": false,
      "x-nullable": false
    },
    "status": {
      "description": "Gets the current iteration status.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "created": {
      "format": "date-time",
      "description": "Gets the time this iteration was completed.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "lastModified": {
      "format": "date-time",
      "description": "Gets the time this iteration was last modified.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "trainedAt": {
      "format": "date-time",
      "description": "Gets the time this iteration was last modified.",
      "type": "string",
      "readOnly": true,
      "x-nullable": true
    },
    "projectId": {
      "format": "uuid",
      "description": "Gets the project id of the iteration.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "exportable": {
      "description": "Whether the iteration can be exported to another format for download.",
      "type": "boolean",
      "readOnly": true,
      "x-nullable": false
    },
    "exportableTo": {
      "description": "A set of platforms this iteration can export to.",
      "type": "array",
      "items": {
        "enum": [
          "CoreML",
          "TensorFlow",
          "DockerFile",
          "ONNX",
          "VAIDK"
        ],
        "type": "string",
        "x-nullable": false
      },
      "readOnly": true
    },
    "domainId": {
      "format": "uuid",
      "description": "Get or sets a guid of the domain the iteration has been trained on.",
      "type": "string",
      "readOnly": true,
      "x-nullable": true
    },
    "classificationType": {
      "description": "Gets the classification type of the project.",
      "enum": [
        "Multiclass",
        "Multilabel"
      ],
      "type": "string",
      "readOnly": true,
      "x-nullable": true,
      "x-ms-enum": {
        "name": "Classifier",
        "modelAsString": true
      }
    },
    "trainingType": {
      "description": "Gets the training type of the iteration.",
      "enum": [
        "Regular",
        "Advanced"
      ],
      "type": "string",
      "readOnly": true,
      "x-nullable": false,
      "x-ms-enum": {
        "name": "TrainingType",
        "modelAsString": true
      }
    },
    "reservedBudgetInHours": {
      "format": "int32",
      "description": "Gets the reserved advanced training budget for the iteration.",
      "type": "integer",
      "readOnly": true,
      "x-nullable": false
    },
    "trainingTimeInMinutes": {
      "format": "int32",
      "description": "Gets the training time for the iteration.",
      "type": "integer",
      "readOnly": true,
      "x-nullable": false
    },
    "publishName": {
      "description": "Name of the published model.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "originalPublishResourceId": {
      "description": "Resource Provider Id this iteration was originally published to.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    }
  }
}

Sample
Schema

<Iteration>
  <id>string</id>
  <name>string</name>
  <status>string</status>
  <created>string</created>
  <lastModified>string</lastModified>
  <trainedAt>string</trainedAt>
  <projectId>string</projectId>
  <exportable>true</exportable>
  <exportableTo>CoreML</exportableTo>
  <domainId>string</domainId>
  <classificationType>Multiclass</classificationType>
  <trainingType>Regular</trainingType>
  <reservedBudgetInHours>0</reservedBudgetInHours>
  <trainingTimeInMinutes>0</trainingTimeInMinutes>
  <publishName>string</publishName>
  <originalPublishResourceId>string</originalPublishResourceId>
</Iteration>

{
  "description": "Iteration model to be sent over JSON.",
  "required": [
    "name"
  ],
  "type": "object",
  "properties": {
    "id": {
      "format": "uuid",
      "description": "Gets the id of the iteration.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "name": {
      "description": "Gets or sets the name of the iteration.",
      "type": "string",
      "readOnly": false,
      "x-nullable": false
    },
    "status": {
      "description": "Gets the current iteration status.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "created": {
      "format": "date-time",
      "description": "Gets the time this iteration was completed.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "lastModified": {
      "format": "date-time",
      "description": "Gets the time this iteration was last modified.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "trainedAt": {
      "format": "date-time",
      "description": "Gets the time this iteration was last modified.",
      "type": "string",
      "readOnly": true,
      "x-nullable": true
    },
    "projectId": {
      "format": "uuid",
      "description": "Gets the project id of the iteration.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "exportable": {
      "description": "Whether the iteration can be exported to another format for download.",
      "type": "boolean",
      "readOnly": true,
      "x-nullable": false
    },
    "exportableTo": {
      "description": "A set of platforms this iteration can export to.",
      "type": "array",
      "items": {
        "enum": [
          "CoreML",
          "TensorFlow",
          "DockerFile",
          "ONNX",
          "VAIDK"
        ],
        "type": "string",
        "x-nullable": false
      },
      "readOnly": true
    },
    "domainId": {
      "format": "uuid",
      "description": "Get or sets a guid of the domain the iteration has been trained on.",
      "type": "string",
      "readOnly": true,
      "x-nullable": true
    },
    "classificationType": {
      "description": "Gets the classification type of the project.",
      "enum": [
        "Multiclass",
        "Multilabel"
      ],
      "type": "string",
      "readOnly": true,
      "x-nullable": true,
      "x-ms-enum": {
        "name": "Classifier",
        "modelAsString": true
      }
    },
    "trainingType": {
      "description": "Gets the training type of the iteration.",
      "enum": [
        "Regular",
        "Advanced"
      ],
      "type": "string",
      "readOnly": true,
      "x-nullable": false,
      "x-ms-enum": {
        "name": "TrainingType",
        "modelAsString": true
      }
    },
    "reservedBudgetInHours": {
      "format": "int32",
      "description": "Gets the reserved advanced training budget for the iteration.",
      "type": "integer",
      "readOnly": true,
      "x-nullable": false
    },
    "trainingTimeInMinutes": {
      "format": "int32",
      "description": "Gets the training time for the iteration.",
      "type": "integer",
      "readOnly": true,
      "x-nullable": false
    },
    "publishName": {
      "description": "Name of the published model.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    },
    "originalPublishResourceId": {
      "description": "Resource Provider Id this iteration was originally published to.",
      "type": "string",
      "readOnly": true,
      "x-nullable": false
    }
  }
}

Response 500

Error response

Sample
Schema

{
  "code": "NoError",
  "message": "string"
}

{
  "required": [
    "code",
    "message"
  ],
  "type": "object",
  "properties": {
    "code": {
      "description": "The error code.",
      "enum": [
        "NoError",
        "BadRequest",
        "BadRequestExceededBatchSize",
        "BadRequestNotSupported",
        "BadRequestInvalidIds",
        "BadRequestProjectName",
        "BadRequestProjectNameNotUnique",
        "BadRequestProjectDescription",
        "BadRequestProjectUnknownDomain",
        "BadRequestProjectUnknownClassification",
        "BadRequestProjectUnsupportedDomainTypeChange",
        "BadRequestProjectUnsupportedExportPlatform",
        "BadRequestProjectImagePreprocessingSettings",
        "BadRequestIterationName",
        "BadRequestIterationNameNotUnique",
        "BadRequestIterationDescription",
        "BadRequestIterationIsNotTrained",
        "BadRequestWorkspaceCannotBeModified",
        "BadRequestWorkspaceNotDeletable",
        "BadRequestTagName",
        "BadRequestTagNameNotUnique",
        "BadRequestTagDescription",
        "BadRequestTagType",
        "BadRequestMultipleNegativeTag",
        "BadRequestImageTags",
        "BadRequestImageRegions",
        "BadRequestNegativeAndRegularTagOnSameImage",
        "BadRequestRequiredParamIsNull",
        "BadRequestIterationIsPublished",
        "BadRequestInvalidPublishName",
        "BadRequestInvalidPublishTarget",
        "BadRequestUnpublishFailed",
        "BadRequestIterationNotPublished",
        "BadRequestSubscriptionApi",
        "BadRequestExceedProjectLimit",
        "BadRequestExceedIterationPerProjectLimit",
        "BadRequestExceedTagPerProjectLimit",
        "BadRequestExceedTagPerImageLimit",
        "BadRequestExceededQuota",
        "BadRequestCannotMigrateProjectWithName",
        "BadRequestNotLimitedTrial",
        "BadRequestImageBatch",
        "BadRequestImageStream",
        "BadRequestImageUrl",
        "BadRequestImageFormat",
        "BadRequestImageSizeBytes",
        "BadRequestImageExceededCount",
        "BadRequestTrainingNotNeeded",
        "BadRequestTrainingNotNeededButTrainingPipelineUpdated",
        "BadRequestTrainingValidationFailed",
        "BadRequestClassificationTrainingValidationFailed",
        "BadRequestMultiClassClassificationTrainingValidationFailed",
        "BadRequestMultiLabelClassificationTrainingValidationFailed",
        "BadRequestDetectionTrainingValidationFailed",
        "BadRequestTrainingAlreadyInProgress",
        "BadRequestDetectionTrainingNotAllowNegativeTag",
        "BadRequestInvalidEmailAddress",
        "BadRequestDomainNotSupportedForAdvancedTraining",
        "BadRequestExportPlatformNotSupportedForAdvancedTraining",
        "BadRequestReservedBudgetInHoursNotEnoughForAdvancedTraining",
        "BadRequestExportValidationFailed",
        "BadRequestExportAlreadyInProgress",
        "BadRequestPredictionIdsMissing",
        "BadRequestPredictionIdsExceededCount",
        "BadRequestPredictionTagsExceededCount",
        "BadRequestPredictionResultsExceededCount",
        "BadRequestPredictionInvalidApplicationName",
        "BadRequestPredictionInvalidQueryParameters",
        "BadRequestInvalid",
        "UnsupportedMediaType",
        "Forbidden",
        "ForbiddenUser",
        "ForbiddenUserResource",
        "ForbiddenUserSignupDisabled",
        "ForbiddenUserSignupAllowanceExceeded",
        "ForbiddenUserDoesNotExist",
        "ForbiddenUserDisabled",
        "ForbiddenUserInsufficientCapability",
        "ForbiddenDRModeEnabled",
        "ForbiddenInvalid",
        "NotFound",
        "NotFoundProject",
        "NotFoundProjectDefaultIteration",
        "NotFoundIteration",
        "NotFoundIterationPerformance",
        "NotFoundTag",
        "NotFoundImage",
        "NotFoundDomain",
        "NotFoundApimSubscription",
        "NotFoundInvalid",
        "Conflict",
        "ConflictInvalid",
        "ErrorUnknown",
        "ErrorProjectInvalidWorkspace",
        "ErrorProjectInvalidPipelineConfiguration",
        "ErrorProjectInvalidDomain",
        "ErrorProjectTrainingRequestFailed",
        "ErrorProjectExportRequestFailed",
        "ErrorFeaturizationServiceUnavailable",
        "ErrorFeaturizationQueueTimeout",
        "ErrorFeaturizationInvalidFeaturizer",
        "ErrorFeaturizationAugmentationUnavailable",
        "ErrorFeaturizationUnrecognizedJob",
        "ErrorFeaturizationAugmentationError",
        "ErrorExporterInvalidPlatform",
        "ErrorExporterInvalidFeaturizer",
        "ErrorExporterInvalidClassifier",
        "ErrorPredictionServiceUnavailable",
        "ErrorPredictionModelNotFound",
        "ErrorPredictionModelNotCached",
        "ErrorPrediction",
        "ErrorPredictionStorage",
        "ErrorRegionProposal",
        "ErrorInvalid"
      ],
      "type": "string",
      "x-ms-enum": {
        "name": "CustomVisionErrorCodes",
        "modelAsString": true
      }
    },
    "message": {
      "description": "A message explaining the error reported by the service.",
      "type": "string"
    }
  }
}

Sample
Schema

<CustomVisionError>
  <code>NoError</code>
  <message>string</message>
</CustomVisionError>

{
  "required": [
    "code",
    "message"
  ],
  "type": "object",
  "properties": {
    "code": {
      "description": "The error code.",
      "enum": [
        "NoError",
        "BadRequest",
        "BadRequestExceededBatchSize",
        "BadRequestNotSupported",
        "BadRequestInvalidIds",
        "BadRequestProjectName",
        "BadRequestProjectNameNotUnique",
        "BadRequestProjectDescription",
        "BadRequestProjectUnknownDomain",
        "BadRequestProjectUnknownClassification",
        "BadRequestProjectUnsupportedDomainTypeChange",
        "BadRequestProjectUnsupportedExportPlatform",
        "BadRequestProjectImagePreprocessingSettings",
        "BadRequestIterationName",
        "BadRequestIterationNameNotUnique",
        "BadRequestIterationDescription",
        "BadRequestIterationIsNotTrained",
        "BadRequestWorkspaceCannotBeModified",
        "BadRequestWorkspaceNotDeletable",
        "BadRequestTagName",
        "BadRequestTagNameNotUnique",
        "BadRequestTagDescription",
        "BadRequestTagType",
        "BadRequestMultipleNegativeTag",
        "BadRequestImageTags",
        "BadRequestImageRegions",
        "BadRequestNegativeAndRegularTagOnSameImage",
        "BadRequestRequiredParamIsNull",
        "BadRequestIterationIsPublished",
        "BadRequestInvalidPublishName",
        "BadRequestInvalidPublishTarget",
        "BadRequestUnpublishFailed",
        "BadRequestIterationNotPublished",
        "BadRequestSubscriptionApi",
        "BadRequestExceedProjectLimit",
        "BadRequestExceedIterationPerProjectLimit",
        "BadRequestExceedTagPerProjectLimit",
        "BadRequestExceedTagPerImageLimit",
        "BadRequestExceededQuota",
        "BadRequestCannotMigrateProjectWithName",
        "BadRequestNotLimitedTrial",
        "BadRequestImageBatch",
        "BadRequestImageStream",
        "BadRequestImageUrl",
        "BadRequestImageFormat",
        "BadRequestImageSizeBytes",
        "BadRequestImageExceededCount",
        "BadRequestTrainingNotNeeded",
        "BadRequestTrainingNotNeededButTrainingPipelineUpdated",
        "BadRequestTrainingValidationFailed",
        "BadRequestClassificationTrainingValidationFailed",
        "BadRequestMultiClassClassificationTrainingValidationFailed",
        "BadRequestMultiLabelClassificationTrainingValidationFailed",
        "BadRequestDetectionTrainingValidationFailed",
        "BadRequestTrainingAlreadyInProgress",
        "BadRequestDetectionTrainingNotAllowNegativeTag",
        "BadRequestInvalidEmailAddress",
        "BadRequestDomainNotSupportedForAdvancedTraining",
        "BadRequestExportPlatformNotSupportedForAdvancedTraining",
        "BadRequestReservedBudgetInHoursNotEnoughForAdvancedTraining",
        "BadRequestExportValidationFailed",
        "BadRequestExportAlreadyInProgress",
        "BadRequestPredictionIdsMissing",
        "BadRequestPredictionIdsExceededCount",
        "BadRequestPredictionTagsExceededCount",
        "BadRequestPredictionResultsExceededCount",
        "BadRequestPredictionInvalidApplicationName",
        "BadRequestPredictionInvalidQueryParameters",
        "BadRequestInvalid",
        "UnsupportedMediaType",
        "Forbidden",
        "ForbiddenUser",
        "ForbiddenUserResource",
        "ForbiddenUserSignupDisabled",
        "ForbiddenUserSignupAllowanceExceeded",
        "ForbiddenUserDoesNotExist",
        "ForbiddenUserDisabled",
        "ForbiddenUserInsufficientCapability",
        "ForbiddenDRModeEnabled",
        "ForbiddenInvalid",
        "NotFound",
        "NotFoundProject",
        "NotFoundProjectDefaultIteration",
        "NotFoundIteration",
        "NotFoundIterationPerformance",
        "NotFoundTag",
        "NotFoundImage",
        "NotFoundDomain",
        "NotFoundApimSubscription",
        "NotFoundInvalid",
        "Conflict",
        "ConflictInvalid",
        "ErrorUnknown",
        "ErrorProjectInvalidWorkspace",
        "ErrorProjectInvalidPipelineConfiguration",
        "ErrorProjectInvalidDomain",
        "ErrorProjectTrainingRequestFailed",
        "ErrorProjectExportRequestFailed",
        "ErrorFeaturizationServiceUnavailable",
        "ErrorFeaturizationQueueTimeout",
        "ErrorFeaturizationInvalidFeaturizer",
        "ErrorFeaturizationAugmentationUnavailable",
        "ErrorFeaturizationUnrecognizedJob",
        "ErrorFeaturizationAugmentationError",
        "ErrorExporterInvalidPlatform",
        "ErrorExporterInvalidFeaturizer",
        "ErrorExporterInvalidClassifier",
        "ErrorPredictionServiceUnavailable",
        "ErrorPredictionModelNotFound",
        "ErrorPredictionModelNotCached",
        "ErrorPrediction",
        "ErrorPredictionStorage",
        "ErrorRegionProposal",
        "ErrorInvalid"
      ],
      "type": "string",
      "x-ms-enum": {
        "name": "CustomVisionErrorCodes",
        "modelAsString": true
      }
    },
    "message": {
      "description": "A message explaining the error reported by the service.",
      "type": "string"
    }
  }
}

Sample
Schema

<CustomVisionError>
  <code>NoError</code>
  <message>string</message>
</CustomVisionError>

{
  "required": [
    "code",
    "message"
  ],
  "type": "object",
  "properties": {
    "code": {
      "description": "The error code.",
      "enum": [
        "NoError",
        "BadRequest",
        "BadRequestExceededBatchSize",
        "BadRequestNotSupported",
        "BadRequestInvalidIds",
        "BadRequestProjectName",
        "BadRequestProjectNameNotUnique",
        "BadRequestProjectDescription",
        "BadRequestProjectUnknownDomain",
        "BadRequestProjectUnknownClassification",
        "BadRequestProjectUnsupportedDomainTypeChange",
        "BadRequestProjectUnsupportedExportPlatform",
        "BadRequestProjectImagePreprocessingSettings",
        "BadRequestIterationName",
        "BadRequestIterationNameNotUnique",
        "BadRequestIterationDescription",
        "BadRequestIterationIsNotTrained",
        "BadRequestWorkspaceCannotBeModified",
        "BadRequestWorkspaceNotDeletable",
        "BadRequestTagName",
        "BadRequestTagNameNotUnique",
        "BadRequestTagDescription",
        "BadRequestTagType",
        "BadRequestMultipleNegativeTag",
        "BadRequestImageTags",
        "BadRequestImageRegions",
        "BadRequestNegativeAndRegularTagOnSameImage",
        "BadRequestRequiredParamIsNull",
        "BadRequestIterationIsPublished",
        "BadRequestInvalidPublishName",
        "BadRequestInvalidPublishTarget",
        "BadRequestUnpublishFailed",
        "BadRequestIterationNotPublished",
        "BadRequestSubscriptionApi",
        "BadRequestExceedProjectLimit",
        "BadRequestExceedIterationPerProjectLimit",
        "BadRequestExceedTagPerProjectLimit",
        "BadRequestExceedTagPerImageLimit",
        "BadRequestExceededQuota",
        "BadRequestCannotMigrateProjectWithName",
        "BadRequestNotLimitedTrial",
        "BadRequestImageBatch",
        "BadRequestImageStream",
        "BadRequestImageUrl",
        "BadRequestImageFormat",
        "BadRequestImageSizeBytes",
        "BadRequestImageExceededCount",
        "BadRequestTrainingNotNeeded",
        "BadRequestTrainingNotNeededButTrainingPipelineUpdated",
        "BadRequestTrainingValidationFailed",
        "BadRequestClassificationTrainingValidationFailed",
        "BadRequestMultiClassClassificationTrainingValidationFailed",
        "BadRequestMultiLabelClassificationTrainingValidationFailed",
        "BadRequestDetectionTrainingValidationFailed",
        "BadRequestTrainingAlreadyInProgress",
        "BadRequestDetectionTrainingNotAllowNegativeTag",
        "BadRequestInvalidEmailAddress",
        "BadRequestDomainNotSupportedForAdvancedTraining",
        "BadRequestExportPlatformNotSupportedForAdvancedTraining",
        "BadRequestReservedBudgetInHoursNotEnoughForAdvancedTraining",
        "BadRequestExportValidationFailed",
        "BadRequestExportAlreadyInProgress",
        "BadRequestPredictionIdsMissing",
        "BadRequestPredictionIdsExceededCount",
        "BadRequestPredictionTagsExceededCount",
        "BadRequestPredictionResultsExceededCount",
        "BadRequestPredictionInvalidApplicationName",
        "BadRequestPredictionInvalidQueryParameters",
        "BadRequestInvalid",
        "UnsupportedMediaType",
        "Forbidden",
        "ForbiddenUser",
        "ForbiddenUserResource",
        "ForbiddenUserSignupDisabled",
        "ForbiddenUserSignupAllowanceExceeded",
        "ForbiddenUserDoesNotExist",
        "ForbiddenUserDisabled",
        "ForbiddenUserInsufficientCapability",
        "ForbiddenDRModeEnabled",
        "ForbiddenInvalid",
        "NotFound",
        "NotFoundProject",
        "NotFoundProjectDefaultIteration",
        "NotFoundIteration",
        "NotFoundIterationPerformance",
        "NotFoundTag",
        "NotFoundImage",
        "NotFoundDomain",
        "NotFoundApimSubscription",
        "NotFoundInvalid",
        "Conflict",
        "ConflictInvalid",
        "ErrorUnknown",
        "ErrorProjectInvalidWorkspace",
        "ErrorProjectInvalidPipelineConfiguration",
        "ErrorProjectInvalidDomain",
        "ErrorProjectTrainingRequestFailed",
        "ErrorProjectExportRequestFailed",
        "ErrorFeaturizationServiceUnavailable",
        "ErrorFeaturizationQueueTimeout",
        "ErrorFeaturizationInvalidFeaturizer",
        "ErrorFeaturizationAugmentationUnavailable",
        "ErrorFeaturizationUnrecognizedJob",
        "ErrorFeaturizationAugmentationError",
        "ErrorExporterInvalidPlatform",
        "ErrorExporterInvalidFeaturizer",
        "ErrorExporterInvalidClassifier",
        "ErrorPredictionServiceUnavailable",
        "ErrorPredictionModelNotFound",
        "ErrorPredictionModelNotCached",
        "ErrorPrediction",
        "ErrorPredictionStorage",
        "ErrorRegionProposal",
        "ErrorInvalid"
      ],
      "type": "string",
      "x-ms-enum": {
        "name": "CustomVisionErrorCodes",
        "modelAsString": true
      }
    },
    "message": {
      "description": "A message explaining the error reported by the service.",
      "type": "string"
    }
  }
}

Code samples

@ECHO OFF

curl -v -X POST "https://*.cognitiveservices.azure.com/customvision/v3.1/training/projects/{projectId}/train?trainingType={string}&reservedBudgetInHours=0&forceTrain=False&notificationEmailAddress={string}"
-H "Training-Key: "
-H "Training-key: {subscription key}"

--data-ascii "{body}"

using System;
using System.Net.Http.Headers;
using System.Text;
using System.Net.Http;
using System.Web;

namespace CSHttpClientSample
{
    static class Program
    {
        static void Main()
        {
            MakeRequest();
            Console.WriteLine("Hit ENTER to exit...");
            Console.ReadLine();
        }
        
        static async void MakeRequest()
        {
            var client = new HttpClient();
            var queryString = HttpUtility.ParseQueryString(string.Empty);

            // Request headers
            client.DefaultRequestHeaders.Add("Training-Key", "");
            client.DefaultRequestHeaders.Add("Training-key", "{subscription key}");

            // Request parameters
            queryString["trainingType"] = "{string}";
            queryString["reservedBudgetInHours"] = "0";
            queryString["forceTrain"] = "False";
            queryString["notificationEmailAddress"] = "{string}";
            var uri = "https://*.cognitiveservices.azure.com/customvision/v3.1/training/projects/{projectId}/train?" + queryString;

            HttpResponseMessage response;

            // Request body
            byte[] byteData = Encoding.UTF8.GetBytes("{body}");

            using (var content = new ByteArrayContent(byteData))
            {
               content.Headers.ContentType = new MediaTypeHeaderValue("< your content type, i.e. application/json >");
               response = await client.PostAsync(uri, content);
            }

        }
    }
}

// // This sample uses the Apache HTTP client from HTTP Components (http://hc.apache.org/httpcomponents-client-ga/)
import java.net.URI;
import org.apache.http.HttpEntity;
import org.apache.http.HttpResponse;
import org.apache.http.client.HttpClient;
import org.apache.http.client.methods.HttpGet;
import org.apache.http.client.utils.URIBuilder;
import org.apache.http.impl.client.HttpClients;
import org.apache.http.util.EntityUtils;

public class JavaSample 
{
    public static void main(String[] args) 
    {
        HttpClient httpclient = HttpClients.createDefault();

        try
        {
            URIBuilder builder = new URIBuilder("https://*.cognitiveservices.azure.com/customvision/v3.1/training/projects/{projectId}/train");

            builder.setParameter("trainingType", "{string}");
            builder.setParameter("reservedBudgetInHours", "0");
            builder.setParameter("forceTrain", "False");
            builder.setParameter("notificationEmailAddress", "{string}");

            URI uri = builder.build();
            HttpPost request = new HttpPost(uri);
            request.setHeader("Training-Key", "");
            request.setHeader("Training-key", "{subscription key}");


            // Request body
            StringEntity reqEntity = new StringEntity("{body}");
            request.setEntity(reqEntity);

            HttpResponse response = httpclient.execute(request);
            HttpEntity entity = response.getEntity();

            if (entity != null) 
            {
                System.out.println(EntityUtils.toString(entity));
            }
        }
        catch (Exception e)
        {
            System.out.println(e.getMessage());
        }
    }
}

<!DOCTYPE html>
<html>
<head>
    <title>JSSample</title>
    <script src="http://ajax.googleapis.com/ajax/libs/jquery/1.9.0/jquery.min.js"></script>
</head>
<body>

<script type="text/javascript">
    $(function() {
        var params = {
            // Request parameters
            "trainingType": "{string}",
            "reservedBudgetInHours": "0",
            "forceTrain": "False",
            "notificationEmailAddress": "{string}",
        };
      
        $.ajax({
            url: "https://*.cognitiveservices.azure.com/customvision/v3.1/training/projects/{projectId}/train?" + $.param(params),
            beforeSend: function(xhrObj){
                // Request headers
                xhrObj.setRequestHeader("Training-Key","");
                xhrObj.setRequestHeader("Training-key","{subscription key}");
            },
            type: "POST",
            // Request body
            data: "{body}",
        })
        .done(function(data) {
            alert("success");
        })
        .fail(function() {
            alert("error");
        });
    });
</script>
</body>
</html>

#import <Foundation/Foundation.h>

int main(int argc, const char * argv[])
{
    NSAutoreleasePool * pool = [[NSAutoreleasePool alloc] init];
    
    NSString* path = @"https://*.cognitiveservices.azure.com/customvision/v3.1/training/projects/{projectId}/train";
    NSArray* array = @[
                         // Request parameters
                         @"entities=true",
                         @"trainingType={string}",
                         @"reservedBudgetInHours=0",
                         @"forceTrain=False",
                         @"notificationEmailAddress={string}",
                      ];
    
    NSString* string = [array componentsJoinedByString:@"&"];
    path = [path stringByAppendingFormat:@"?%@", string];

    NSLog(@"%@", path);

    NSMutableURLRequest* _request = [NSMutableURLRequest requestWithURL:[NSURL URLWithString:path]];
    [_request setHTTPMethod:@"POST"];
    // Request headers
    [_request setValue:@"" forHTTPHeaderField:@"Training-Key"];
    [_request setValue:@"{subscription key}" forHTTPHeaderField:@"Training-key"];
    // Request body
    [_request setHTTPBody:[@"{body}" dataUsingEncoding:NSUTF8StringEncoding]];
    
    NSURLResponse *response = nil;
    NSError *error = nil;
    NSData* _connectionData = [NSURLConnection sendSynchronousRequest:_request returningResponse:&response error:&error];

    if (nil != error)
    {
        NSLog(@"Error: %@", error);
    }
    else
    {
        NSError* error = nil;
        NSMutableDictionary* json = nil;
        NSString* dataString = [[NSString alloc] initWithData:_connectionData encoding:NSUTF8StringEncoding];
        NSLog(@"%@", dataString);
        
        if (nil != _connectionData)
        {
            json = [NSJSONSerialization JSONObjectWithData:_connectionData options:NSJSONReadingMutableContainers error:&error];
        }
        
        if (error || !json)
        {
            NSLog(@"Could not parse loaded json with error:%@", error);
        }
        
        NSLog(@"%@", json);
        _connectionData = nil;
    }
    
    [pool drain];

    return 0;
}

<?php
// This sample uses the Apache HTTP client from HTTP Components (http://hc.apache.org/httpcomponents-client-ga/)
require_once 'HTTP/Request2.php';

$request = new Http_Request2('https://*.cognitiveservices.azure.com/customvision/v3.1/training/projects/{projectId}/train');
$url = $request->getUrl();

$headers = array(
    // Request headers
    'Training-Key' => '',
    'Training-key' => '{subscription key}',
);

$request->setHeader($headers);

$parameters = array(
    // Request parameters
    'trainingType' => '{string}',
    'reservedBudgetInHours' => '0',
    'forceTrain' => 'False',
    'notificationEmailAddress' => '{string}',
);

$url->setQueryVariables($parameters);

$request->setMethod(HTTP_Request2::METHOD_POST);

// Request body
$request->setBody("{body}");

try
{
    $response = $request->send();
    echo $response->getBody();
}
catch (HttpException $ex)
{
    echo $ex;
}

?>

########### Python 2.7 #############
import httplib, urllib, base64

headers = {
    # Request headers
    'Training-Key': '',
    'Training-key': '{subscription key}',
}

params = urllib.urlencode({
    # Request parameters
    'trainingType': '{string}',
    'reservedBudgetInHours': '0',
    'forceTrain': 'False',
    'notificationEmailAddress': '{string}',
})

try:
    conn = httplib.HTTPSConnection('*.cognitiveservices.azure.com')
    conn.request("POST", "/customvision/v3.1/training/projects/{projectId}/train?%s" % params, "{body}", headers)
    response = conn.getresponse()
    data = response.read()
    print(data)
    conn.close()
except Exception as e:
    print("[Errno {0}] {1}".format(e.errno, e.strerror))

####################################

########### Python 3.2 #############
import http.client, urllib.request, urllib.parse, urllib.error, base64

headers = {
    # Request headers
    'Training-Key': '',
    'Training-key': '{subscription key}',
}

params = urllib.parse.urlencode({
    # Request parameters
    'trainingType': '{string}',
    'reservedBudgetInHours': '0',
    'forceTrain': 'False',
    'notificationEmailAddress': '{string}',
})

try:
    conn = http.client.HTTPSConnection('*.cognitiveservices.azure.com')
    conn.request("POST", "/customvision/v3.1/training/projects/{projectId}/train?%s" % params, "{body}", headers)
    response = conn.getresponse()
    data = response.read()
    print(data)
    conn.close()
except Exception as e:
    print("[Errno {0}] {1}".format(e.errno, e.strerror))

####################################

require 'net/http'

uri = URI('https://*.cognitiveservices.azure.com/customvision/v3.1/training/projects/{projectId}/train')
uri.query = URI.encode_www_form({
    # Request parameters
    'trainingType' => '{string}',
    'reservedBudgetInHours' => '0',
    'forceTrain' => 'False',
    'notificationEmailAddress' => '{string}'
})

request = Net::HTTP::Post.new(uri.request_uri)
# Request headers
request['Training-Key'] = ''
# Request headers
request['Training-key'] = '{subscription key}'
# Request body
request.body = "{body}"

response = Net::HTTP.start(uri.host, uri.port, :use_ssl => uri.scheme == 'https') do |http|
    http.request(request)
end

puts response.body