swagger: '2.0' info: title: Microsoft Azure Computer Vision Client description: >- The Computer Vision API provides state-of-the-art algorithms to process images and return information. For example, it can be used to extract text using Read OCR, caption an image using descriptive natural language, detect objects, people, and more. version: 2023-04-01-preview paths: /imageanalysis:segment: post: tags: - Operations summary: >- Microsoft Azure Analyze The Input Image The Request Either Contains An Image Stream With Any Content Type [ Image * , Application Octet Stream ], Or A Json Payload Which Includes A Url Property To Be Used To Retrieve The Image Stream An Image Stream Of Content Type Image Png Is Returned, Where The Pixel Values Depend On The Analysis Mode The Returned Image Has The Same Dimensions As The Input Image For Modes: Foregroundmatting The Returned Image Has The Same Aspect Ratio And Same Dimensions As The Input Image Up To A Limit Of 16 Megapixels For Modes: Backgroundremoval operationId: microsoftAzureImageanalysisSegment consumes: - application/json produces: - image/png - application/json parameters: - in: query name: mode description: The analysis mode requested. type: string enum: - backgroundRemoval - foregroundMatting x-ms-enum: name: SegmentationMode modelAsString: true - $ref: '#/parameters/ApiVersion' - in: body name: body description: >- A JSON document with a URL pointing to the image that is to be analyzed. required: true schema: $ref: '#/definitions/ImageUrl' responses: '200': description: Success schema: type: file default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: Segment_BackgroundRemoval_FromImageUrl: $ref: ./examples/Segment_BackgroundRemoval_FromImageUrl.json Segment_ForegroundMatting_FromImageUrl: $ref: ./examples/Segment_ForegroundMatting_FromImageUrl.json description: Needs a more full description created. /retrieval:vectorizeText: post: tags: - ImageRetrieval summary: 'Microsoft Azure Return Vector From A Text' operationId: microsoftAzureImageretrievalVectorizetext consumes: - application/json produces: - application/json parameters: - in: query name: model-version description: Model version. type: string - $ref: '#/parameters/ApiVersion' - in: body name: body description: Request of VectorizeText. schema: $ref: '#/definitions/VectorizeTextRequestApiModel' responses: '200': description: Success schema: $ref: '#/definitions/SingleVectorResultApiModel' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: ImageRetrieval_VectorizeText: $ref: ./examples/ImageRetrieval_VectorizeText.json description: Needs a more full description created. /retrieval:vectorizeImage: post: tags: - ImageRetrieval summary: 'Microsoft Azure Return Vector From An Image' operationId: microsoftAzureImageretrievalVectorizeimage consumes: - application/json produces: - application/json parameters: - in: query name: model-version description: Model version. type: string - $ref: '#/parameters/ApiVersion' - in: body name: body description: >- A JSON document with a URL pointing to the image that is to be analyzed. required: true schema: $ref: '#/definitions/ImageUrl' responses: '200': description: Success schema: $ref: '#/definitions/SingleVectorResultApiModel' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: ImageRetrieval_VectorizeImage: $ref: ./examples/ImageRetrieval_VectorizeImage.json description: Needs a more full description created. /imagecomposition:stitch: post: tags: - Operations summary: 'Microsoft Azure Run The Image Stitching Operation Against A Sequence Of Images' operationId: microsoftAzureImagecompositionStitch consumes: - application/json-patch+json produces: - image/jpeg - application/json parameters: - $ref: '#/parameters/ApiVersion' - in: body name: body description: Input images urls that pass into image stitching operation. required: true schema: $ref: '#/definitions/ImageStitchingRequestApiModel' responses: '200': description: Success schema: type: file default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: ImageComposition_Stitch: $ref: ./examples/ImageComposition_Stitch.json description: Needs a more full description created. /imagecomposition:rectify: post: tags: - Operations summary: >- Microsoft Azure Run The Image Rectification Operation Against An Image With 4 Control Points Provided In The Parameter operationId: microsoftAzureImagecompositionRectify consumes: - application/json-patch+json produces: - image/jpeg - application/json parameters: - $ref: '#/parameters/ApiVersion' - in: body name: body description: >- Input image url and control points that are passed into rectification operation. required: true schema: $ref: '#/definitions/ImageRectificationRequestApiModel' responses: '200': description: Success schema: type: file default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: ImageComposition_Rectify: $ref: ./examples/ImageComposition_Rectify.json description: Needs a more full description created. /planogramcompliance:match: post: tags: - Operations summary: >- Microsoft Azure Run The Planogram Matching Operation Against A Planogram And A Product Understanding Result operationId: microsoftAzurePlanogramcomplianceMatch consumes: - application/json-patch+json produces: - application/json parameters: - $ref: '#/parameters/ApiVersion' - in: body name: body description: Input to pass into the planogram matching operation. schema: $ref: '#/definitions/PlanogramMatchingRequestApiModel' responses: '200': description: Success schema: $ref: '#/definitions/PlanogramMatchingResultApiModel' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: PlanogramCompliance_Match: $ref: ./examples/PlanogramCompliance_Match.json description: Needs a more full description created. /productrecognition/{modelName}/runs/{runName}: put: tags: - Operations summary: 'Microsoft Azure Run The Product Recognition Against A Model With An Image' operationId: microsoftAzureProductrecognitionCreate produces: - application/json parameters: - in: path name: modelName description: The name of the model to run product recognition with. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - in: path name: runName description: The name of the product recognition run. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - $ref: '#/parameters/ApiVersion' responses: '201': description: Created schema: $ref: '#/definitions/ProductRecognitionApiModel' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: ProductRecognition_Create: $ref: ./examples/ProductRecognition_Create.json description: Needs a more full description created. get: tags: - Operations summary: 'Microsoft Azure Get Information About A Specific Product Recognition Run' operationId: microsoftAzureProductrecognitionGet produces: - application/json parameters: - in: path name: modelName description: The name of the model the product recognition run belongs to. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - in: path name: runName description: The name of the product recognition run. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - $ref: '#/parameters/ApiVersion' responses: '200': description: Success schema: $ref: '#/definitions/ProductRecognitionApiModel' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: ProductRecognition_Get: $ref: ./examples/ProductRecognition_Get.json description: Needs a more full description created. delete: tags: - Operations summary: "Microsoft Azure Delete A Product Recognition Run A Product Recognition Run Can Be Deleted If It Is In The Succeeded Or Failed States \r\n \r\nstatus Codes Returned:\r\n 204: Operation Completed Successfully \r\n 400: The Request Was Malformed \r\n 404: A Product Recognition Run With The Specified Name Was Not Found" operationId: microsoftAzureProductrecognitionDelete produces: - application/json parameters: - in: path name: modelName description: The name of the model to delete the product recognition run for. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - in: path name: runName description: The name of the product recognition run. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - $ref: '#/parameters/ApiVersion' responses: '204': description: No Content default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: ProductRecognition_Delete: $ref: ./examples/ProductRecognition_Delete.json description: Needs a more full description created. /productrecognition/{modelName}/runs: get: tags: - Operations summary: 'Microsoft Azure List All Product Recognition Run Of A Model' operationId: microsoftAzureProductrecognitionList produces: - application/json parameters: - in: path name: modelName description: The name of the model the product recognition runs belongs to. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - in: query name: skip description: Number of product recognition runs to be skipped. type: integer format: int32 default: 0 maximum: 2147483647 minimum: 0 - in: query name: top description: >- Number of product recognition runs to be returned after skipping. The maximum allowed value is 30. type: integer format: int32 default: 10 maximum: 30 minimum: 1 - $ref: '#/parameters/ApiVersion' responses: '200': description: Success schema: $ref: '#/definitions/ProductRecognitionApiModelCollectionApiModel' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-pageable: nextLinkName: nextLink x-ms-examples: ProductRecognition_List: $ref: ./examples/ProductRecognition_List.json description: Needs a more full description created. /imageanalysis:analyze: post: tags: - Operations summary: >- Microsoft Azure Analyze The Input Image The Request Either Contains Image Stream With Any Content Type [ Image * , Application Octet Stream ], Or A Json Payload Which Includes An Url Property To Be Used To Retrieve The Image Stream operationId: microsoftAzureImageanalysisAnalyze consumes: - application/json produces: - application/json parameters: - in: query name: features description: >- The visual features requested: tags, objects, caption, denseCaptions, read, smartCrops, people. This parameter needs to be specified if the parameter "model-name" is not specified. type: array items: enum: - tags - caption - denseCaptions - objects - read - smartCrops - people type: string x-ms-enum: name: VisualFeature modelAsString: true collectionFormat: csv - in: query name: model-name description: >- The name of the custom trained model. This parameter needs to be specified if the parameter "features" is not specified. type: string - in: query name: language description: >- The desired language for output generation. If this parameter is not specified, the default value is "en". See https://aka.ms/cv-languages for a list of supported languages. type: string default: en - in: query name: smartcrops-aspect-ratios description: >- A list of aspect ratios to use for smartCrops feature. Aspect ratios are calculated by dividing the target crop width by the height. Supported values are between 0.75 and 1.8 (inclusive). Multiple values should be comma-separated. If this parameter is not specified, the service will return one crop suggestion with an aspect ratio it sees fit between 0.5 and 2.0 (inclusive). type: string - in: query name: gender-neutral-caption description: >- Boolean flag for enabling gender-neutral captioning for caption and denseCaptions features. If this parameter is not specified, the default value is "false". type: boolean default: false - $ref: '#/parameters/ApiVersion' - in: body name: body description: >- A JSON document with a URL pointing to the image that is to be analyzed. required: true schema: $ref: '#/definitions/ImageUrl' responses: '200': description: Success schema: $ref: '#/definitions/ImageAnalysisResult' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: AnalyzeImage_CustomModel: $ref: ./examples/AnalyzeImage_CustomModel.json description: Needs a more full description created. /datasets/{name}: put: tags: - Datasets summary: "Microsoft Azure Register A New Dataset \r\n \r\nstatus Codes Returned:\r\n 201: Operation Completed Successfully \r\n 400: The Request Was Malformed \r\n 409: A Dataset With The Specified Name Already Exists" operationId: microsoftAzureDatasetsRegister consumes: - application/json-patch+json produces: - application/json parameters: - in: path name: name description: >- A name that can be used to uniquely identify the dataset after it has been registered. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - $ref: '#/parameters/ApiVersion' - in: body name: body description: >- Properties for the dataset, such as the list of URIs to the annotation files. required: true schema: $ref: '#/definitions/Dataset' responses: '201': description: Created schema: $ref: '#/definitions/Dataset' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: RegisterDataset_ImageClassification: $ref: ./examples/RegisterDataset_ImageClassification.json description: Needs a more full description created. get: tags: - Datasets summary: "Microsoft Azure Get Information About A Specific Dataset \r\n \r\nstatus Codes Returned:\r\n 200: Operation Completed Successfully \r\n 400: The Request Was Malformed \r\n 404: A Dataset With The Specified Name Was Not Found" operationId: microsoftAzureDatasetsGet produces: - application/json parameters: - in: path name: name description: The name of the dataset to get. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - $ref: '#/parameters/ApiVersion' responses: '200': description: Success schema: $ref: '#/definitions/Dataset' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: Datasets_Get: $ref: ./examples/Datasets_Get.json description: Needs a more full description created. patch: tags: - Datasets summary: "Microsoft Azure Update The Properties Of An Existing Dataset \r\n \r\nstatus Codes Returned:\r\n 200: Operation Completed Successfully \r\n 400: The Request Was Malformed \r\n 404: A Dataset With The Specified Name Was Not Found \r\n 412: An If Match Header Was Provided, But The Given Etag Did Not Match The Current Etag Value" operationId: microsoftAzureDatasetsUpdate consumes: - application/json-patch+json produces: - application/json parameters: - in: path name: name description: The name of the dataset to update. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - in: header name: If-Match description: "Optional ETag for the dataset to update.
\r\nIf an ETag is provided, then the dataset will be updated only if its current ETag value matches the given ETag.\r\nIf the ETag values don't match, then the update operation will fail with status code 412 (Precondition Failed).\r\nThis indicates that the dataset has been updated since the last time information for the dataset was obtained.
\r\nIf an ETag is not provided or its value is '*', then the dataset will always be updated regardless of the current ETag value." type: string - $ref: '#/parameters/ApiVersion' - in: body name: body description: Properties to update on the existing dataset. required: true schema: $ref: '#/definitions/Dataset' responses: '200': description: Success schema: $ref: '#/definitions/Dataset' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: Datasets_Update: $ref: ./examples/Datasets_Update.json description: Needs a more full description created. delete: tags: - Datasets summary: "Microsoft Azure Unregister A Dataset \r\n \r\nstatus Codes Returned:\r\n 204: Operation Completed Successfully \r\n 400: The Request Was Malformed \r\n 404: A Dataset With The Specified Name Was Not Found \r\n 412: An If Match Header Was Provided, But The Given Etag Did Not Match The Current Etag Value" operationId: microsoftAzureDatasetsUnregister produces: - application/json parameters: - in: path name: name description: The name of the dataset to unregister. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - in: header name: If-Match description: "Optional ETag for the dataset to unregister.
\r\nIf an ETag is provided, then the dataset will be unregistered only if its current ETag value matches the given ETag.\r\nIf the ETag values don't match, then the unregister operation will fail with status code 412 (Precondition Failed).\r\nThis indicates that the dataset has been updated since the last time information for the dataset was obtained.
\r\nIf an ETag is not provided or its value is '*', then the dataset will always be unregistered regardless of the current ETag value." type: string - $ref: '#/parameters/ApiVersion' responses: '204': description: No Content default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: Datasets_Unregister: $ref: ./examples/Datasets_Unregister.json description: Needs a more full description created. /datasets: get: tags: - Datasets summary: "Microsoft Azure Get A List Of Datasets That Have Been Registered \r\n \r\nstatus Codes Returned:\r\n 200: Operation Completed Successfully \r\n 400: The Request Was Malformed" operationId: microsoftAzureDatasetsList produces: - application/json parameters: - in: query name: skip description: Number of datasets to be skipped. type: integer format: int32 default: 0 maximum: 2147483647 minimum: 0 - in: query name: top description: >- Number of datasets to be returned after skipping. The maximum allowed value is 30. type: integer format: int32 default: 10 maximum: 30 minimum: 1 - $ref: '#/parameters/ApiVersion' responses: '200': description: Success schema: $ref: '#/definitions/DatasetApiModelCollectionApiModel' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: Datasets_List: $ref: ./examples/Datasets_List.json x-ms-pageable: nextLinkName: nextLink description: Needs a more full description created. /models/{name}: put: tags: - Models summary: "Microsoft Azure Start Training A Custom Model \r\n \r\nstatus Codes Returned:\r\n 201: Operation Completed Successfully \r\n 400: The Request Was Malformed \r\n 409: A Model With The Specified Name Already Exists" operationId: microsoftAzureModelsCreate consumes: - application/json-patch+json produces: - application/json parameters: - in: path name: name description: >- A name that can be used to uniquely identify the model after it has been created. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - $ref: '#/parameters/ApiVersion' - in: body name: body description: >- Properties for the model, such as the name of the dataset to use to train the model. required: true schema: $ref: '#/definitions/Model' responses: '201': description: Created schema: $ref: '#/definitions/Model' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: Models_Create: $ref: ./examples/Models_Create.json description: Needs a more full description created. get: tags: - Models summary: "Microsoft Azure Get Information About A Specific Model \r\n \r\nstatus Codes Returned:\r\n 200: Operation Completed Successfully \r\n 400: The Request Was Malformed \r\n 404: A Model With The Specified Name Was Not Found" operationId: microsoftAzureModelsGet produces: - application/json parameters: - in: path name: name description: The name of the model to get. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - $ref: '#/parameters/ApiVersion' responses: '200': description: Success schema: $ref: '#/definitions/Model' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: Models_Get: $ref: ./examples/Models_Get.json description: Needs a more full description created. delete: tags: - Models summary: "Microsoft Azure Delete A Custom Model A Model Can Be Deleted If It Is In One Of The Succeeded , Failed , Or Canceled States \r\nif A Model Is In The Notstarted Or Training State, Cancel Training And Wait For Cancellation To Finish Before Deleting The Model \r\n \r\nstatus Codes Returned:\r\n 204: Operation Completed Successfully \r\n 400: The Request Was Malformed \r\n 404: A Model With The Specified Name Was Not Found" operationId: microsoftAzureModelsDelete produces: - application/json parameters: - in: path name: name description: The name of the model to delete. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - $ref: '#/parameters/ApiVersion' responses: '204': description: No Content default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: Models_Delete: $ref: ./examples/Models_Delete.json description: Needs a more full description created. /models: get: tags: - Models summary: "Microsoft Azure Get A List Of The Available Models \r\n \r\nstatus Codes Returned:\r\n 200: Operation Completed Successfully \r\n 400: The Request Was Malformed" operationId: microsoftAzureModelsList produces: - application/json parameters: - in: query name: skip description: Number of models to be skipped. type: integer format: int32 default: 0 maximum: 2147483647 minimum: 0 - in: query name: top description: >- Number of models to be returned after skipping. The maximum allowed value is 30. type: integer format: int32 default: 10 maximum: 30 minimum: 1 - $ref: '#/parameters/ApiVersion' responses: '200': description: Success schema: $ref: '#/definitions/ModelApiModelCollectionApiModel' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: Models_List: $ref: ./examples/Models_List.json x-ms-pageable: nextLinkName: nextLink description: Needs a more full description created. /models/{name}:cancel: post: tags: - Models summary: "Microsoft Azure Cancel Model Training \r\n \r\nstatus Codes Returned:\r\n 202: Operation Completed Successfully \r\n 400: The Request Was Malformed \r\n 404: A Model With The Specified Name Was Not Found" operationId: microsoftAzureModelsCanceltraining produces: - application/json parameters: - in: path name: name description: The name of the model to cancel training. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - $ref: '#/parameters/ApiVersion' responses: '202': description: Accepted default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: Models_CancelTraining: $ref: ./examples/Models_CancelTraining.json description: Needs a more full description created. /models/{name}/evaluations/{evaluationName}: put: tags: - Models summary: "Microsoft Azure Evaluate An Existing Model \r\n \r\nstatus Codes Returned:\r\n 201: Operation Completed Successfully \r\n 400: The Request Was Malformed \r\n 409: An Evaluation With The Specified Name Already Exists" operationId: microsoftAzureModelevaluationsCreate consumes: - application/json-patch+json produces: - application/json parameters: - in: path name: name description: The name of the model to evaluate. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - in: path name: evaluationName description: >- A name that can be used to uniquely identify the evaluation after it has been created. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - $ref: '#/parameters/ApiVersion' - in: body name: body description: >- Properties for the evaluation, such as the name of the dataset to use to test the model. required: true schema: $ref: '#/definitions/ModelEvaluation' responses: '201': description: Created schema: $ref: '#/definitions/ModelEvaluation' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: ModelEvaluations_Create: $ref: ./examples/ModelEvaluations_Create.json description: Needs a more full description created. get: tags: - Models summary: "Microsoft Azure Get Information About A Specific Model Evaluation \r\n \r\nstatus Codes Returned:\r\n 200: Operation Completed Successfully \r\n 400: The Request Was Malformed \r\n 404: A Model Evaluation With The Specified Name Was Not Found" operationId: microsoftAzureModelevaluationsGet produces: - application/json parameters: - in: path name: name description: The name of the model to get the evaluation for. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - in: path name: evaluationName description: The name of the model evaluation to get. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - $ref: '#/parameters/ApiVersion' responses: '200': description: Success schema: $ref: '#/definitions/ModelEvaluation' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: ModelEvaluations_Get: $ref: ./examples/ModelEvaluations_Get.json description: Needs a more full description created. delete: tags: - Models summary: "Microsoft Azure Delete A Model Evaluation A Model Evaluation Can Be Deleted If It Is In The Succeeded Or Failed States \r\n \r\nstatus Codes Returned:\r\n 204: Operation Completed Successfully \r\n 400: The Request Was Malformed \r\n 404: A Model Evaluation With The Specified Name Was Not Found" operationId: microsoftAzureModelevaluationsDelete produces: - application/json parameters: - in: path name: name description: The name of the model to delete the evaluation for. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - in: path name: evaluationName description: The name of the model evaluation to delete. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - $ref: '#/parameters/ApiVersion' responses: '204': description: No Content default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: ModelEvaluations_Delete: $ref: ./examples/ModelEvaluations_Delete.json description: Needs a more full description created. /models/{name}/evaluations: get: tags: - Models summary: "Microsoft Azure Get A List Of The Available Evaluations For A Model \r\n \r\nstatus Codes Returned:\r\n 200: Operation Completed Successfully \r\n 400: The Request Was Malformed" operationId: microsoftAzureModelevaluationsList produces: - application/json parameters: - in: path name: name description: The name of the model to get evaluations for. required: true type: string maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ - in: query name: skip description: Number of evaluations to be skipped. type: integer format: int32 default: 0 maximum: 2147483647 minimum: 0 - in: query name: top description: >- Number of evaluations to be returned after skipping. The maximum allowed value is 30. type: integer format: int32 default: 10 maximum: 30 minimum: 1 - $ref: '#/parameters/ApiVersion' responses: '200': description: Success schema: $ref: '#/definitions/ModelEvaluationApiModelCollectionApiModel' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: ModelEvaluations_List: $ref: ./examples/ModelEvaluations_List.json x-ms-pageable: nextLinkName: nextLink description: Needs a more full description created. definitions: AdultMatch: description: An object describing adult content match. required: - confidence - isMatch type: object properties: isMatch: description: A value indicating if the image is matched adult content. type: boolean confidence: format: double description: A value indicating the confidence level of matched adult content. maximum: 1 minimum: 0 type: number AdultResult: description: >- An object describing whether the image contains adult-oriented content and/or is racy. required: - adult - gore - racy type: object properties: adult: $ref: '#/definitions/AdultMatch' racy: $ref: '#/definitions/AdultMatch' gore: $ref: '#/definitions/AdultMatch' BoundingBox: description: A bounding box for an area inside an image. required: - h - w - x - 'y' type: object properties: x: format: int32 description: Left-coordinate of the top left point of the area, in pixels. minimum: 0 type: integer 'y': format: int32 description: Top-coordinate of the top left point of the area, in pixels. minimum: 0 type: integer w: format: int32 description: Width measured from the top-left point of the area, in pixels. minimum: 1 type: integer h: format: int32 description: Height measured from the top-left point of the area, in pixels. minimum: 1 type: integer CaptionResult: description: A brief description of what the image depicts. required: - confidence - text type: object properties: text: description: The text of the caption. minLength: 1 type: string confidence: format: double description: The level of confidence the service has in the caption. maximum: 1 minimum: 0 type: number CropRegion: description: >- A region identified for smart cropping. There will be one region returned for each requested aspect ratio. required: - aspectRatio - boundingBox type: object properties: aspectRatio: format: double description: The aspect ratio of the crop region. type: number boundingBox: $ref: '#/definitions/BoundingBox' DenseCaption: description: A brief description of what the image depicts. required: - confidence - text type: object properties: text: description: The text of the caption. minLength: 1 type: string confidence: format: double description: The level of confidence the service has in the caption. maximum: 1 minimum: 0 type: number boundingBox: $ref: '#/definitions/BoundingBox' DenseCaptionsResult: description: A list of captions. required: - values type: object properties: values: description: A list of captions. type: array items: $ref: '#/definitions/DenseCaption' Description: description: A brief description of what the image depicts. required: - confidence - text type: object properties: text: description: The text of the caption. minLength: 1 type: string confidence: format: double description: The level of confidence the service has in the caption. maximum: 1 minimum: 0 type: number DescriptionResult: description: A list of descriptions sorted by confidence level. required: - values type: object properties: values: description: A list of descriptions sorted by confidence level. type: array items: $ref: '#/definitions/Description' DetectedObject: description: Describes a detected object in an image. required: - boundingBox - tags type: object properties: id: description: Id of the detected object. minLength: 1 type: string boundingBox: $ref: '#/definitions/BoundingBox' tags: description: Classification confidences of the detected object. minItems: 1 type: array items: $ref: '#/definitions/Tag' DetectedPerson: description: A person detected in an image. required: - boundingBox - confidence type: object properties: boundingBox: $ref: '#/definitions/BoundingBox' confidence: format: double description: >- Confidence score of having observed the person in the image, as a value ranging from 0 to 1. maximum: 1 minimum: 0 type: number DocumentLanguage: description: An object representing the detected language for a given text span. required: - confidence - languageCode - spans type: object properties: spans: description: >- Location of the text elements in the concatenated content the language applies to. type: array items: $ref: '#/definitions/DocumentSpan' languageCode: description: >- Detected language. Value may an ISO 639-1 language code (ex. "en", "fr") or BCP 47 language tag (ex. "zh-Hans"). minLength: 1 type: string confidence: format: double description: Confidence of correctly identifying the language. maximum: 1 minimum: 0 type: number DocumentLine: description: >- A content line object consisting of an adjacent sequence of content elements, such as words and selection marks. required: - boundingBox - content - spans type: object properties: content: description: Concatenated content of the contained elements in reading order. minLength: 1 type: string boundingBox: description: Bounding box of the line. type: array items: format: double type: number spans: description: Location of the line in the reading order concatenated content. type: array items: $ref: '#/definitions/DocumentSpan' DocumentPage: description: The content and layout elements extracted from a page from the input. required: - angle - height - lines - pageNumber - spans - width - words type: object properties: height: format: double description: The height of the image/PDF in pixels/inches, respectively. type: number width: format: double description: The width of the image/PDF in pixels/inches, respectively. type: number angle: format: double description: >- The general orientation of the content in clockwise direction, measured in degrees between (-180, 180]. type: number pageNumber: format: int32 description: 1-based page number in the input document. type: integer words: description: Extracted words from the page. type: array items: $ref: '#/definitions/DocumentWord' spans: description: Location of the page in the reading order concatenated content. type: array items: $ref: '#/definitions/DocumentSpan' lines: description: >- Extracted lines from the page, potentially containing both textual and visual elements. type: array items: $ref: '#/definitions/DocumentLine' DocumentSpan: description: >- Contiguous region of the concatenated content property, specified as an offset and length. required: - length - offset type: object properties: offset: format: int32 description: Zero-based index of the content represented by the span. type: integer length: format: int32 description: Number of characters in the content represented by the span. type: integer DocumentStyle: description: An object representing observed text styles. required: - spans type: object properties: isHandwritten: description: Is content handwritten or not. type: boolean spans: description: >- Location of the text elements in the concatenated content the style applies to. type: array items: $ref: '#/definitions/DocumentSpan' confidence: format: double description: Confidence of correctly identifying the style. type: number DocumentWord: description: "A word object consisting of a contiguous sequence of characters. For non-space delimited languages,\r\nsuch as Chinese, Japanese, and Korean, each character is represented as its own word." required: - boundingBox - confidence - content - span type: object properties: content: description: Text content of the word. minLength: 1 type: string boundingBox: description: Bounding box of the word. type: array items: format: double type: number confidence: format: double description: Confidence of correctly extracting the word. type: number span: $ref: '#/definitions/DocumentSpan' ErrorResponse: description: Response returned when an error occurs. required: - error type: object properties: error: $ref: '#/definitions/ErrorResponseDetails' ErrorResponseDetails: description: Error info. required: - code - message type: object properties: code: description: Error code. type: string message: description: Error message. type: string target: description: Target of the error. type: string details: description: List of detailed errors. type: array items: $ref: '#/definitions/ErrorResponseDetails' innererror: $ref: '#/definitions/ErrorResponseInnerError' ErrorResponseInnerError: description: Detailed error. required: - code - message type: object properties: code: description: Error code. type: string message: description: Error message. type: string innererror: $ref: '#/definitions/ErrorResponseInnerError' FixtureApiModel: description: Describes a fixture in a planogram. required: - h - id - w - x - 'y' type: object properties: id: description: Id of the fixture. minLength: 1 type: string w: format: double description: Width of the fixture. type: number h: format: double description: Height of the fixture. type: number x: format: double description: Left offset from the origin, in unit of in inches or centimeters. minimum: 0 type: number 'y': format: double description: Top offset from the origin, in unit of in inches or centimeters. minimum: 0 type: number ImageAnalysisResult: description: Describe the combined results of different types of image analysis. required: - metadata - modelVersion type: object properties: customModelResult: $ref: '#/definitions/ImagePredictionResult' captionResult: $ref: '#/definitions/CaptionResult' objectsResult: $ref: '#/definitions/ObjectsResult' readResult: $ref: '#/definitions/ReadResult' denseCaptionsResult: $ref: '#/definitions/DenseCaptionsResult' modelVersion: description: Model Version. minLength: 1 type: string metadata: $ref: '#/definitions/ImageMetadataApiModel' tagsResult: $ref: '#/definitions/TagsResult' adultResult: $ref: '#/definitions/AdultResult' smartCropsResult: $ref: '#/definitions/SmartCropsResult' peopleResult: $ref: '#/definitions/PeopleResult' ImageMetadataApiModel: description: The image metadata information such as height and width. required: - height - width type: object properties: width: format: int32 description: The width of the image in pixels. minimum: 1 type: integer height: format: int32 description: The height of the image in pixels. minimum: 1 type: integer ImagePredictionResult: description: Describes the prediction result of an image. type: object properties: tagsResult: $ref: '#/definitions/TagsResult' objectsResult: $ref: '#/definitions/ObjectsResult' ImageRectificationControlPointsApiModel: description: Four corner control points for rectification. The origin is at top-left. required: - bottomLeft - bottomRight - topLeft - topRight type: object properties: topLeft: $ref: '#/definitions/NormalizedCoordinateApiModel' topRight: $ref: '#/definitions/NormalizedCoordinateApiModel' bottomLeft: $ref: '#/definitions/NormalizedCoordinateApiModel' bottomRight: $ref: '#/definitions/NormalizedCoordinateApiModel' ImageRectificationRequestApiModel: description: Image rectification input. required: - controlPoints - url type: object properties: url: format: uri description: Source image blob URL. type: string controlPoints: $ref: '#/definitions/ImageRectificationControlPointsApiModel' ImageStitchingRequestApiModel: description: Image stitching input. required: - images type: object properties: images: description: Source images to stitch. maxItems: 20 minItems: 2 type: array items: format: uri type: string ImageUrl: description: A JSON document with a URL pointing to the image that is to be analyzed. required: - url type: object properties: url: description: Publicly reachable URL of an image. type: string NormalizedCoordinateApiModel: description: Normalized XY-coordinate. required: - x - 'y' type: object properties: x: format: double description: Horizontal coordinate. maximum: 1 minimum: 0 type: number 'y': format: double description: Vertical coordinate. maximum: 1 minimum: 0 type: number ObjectsResult: description: Describes detected objects in an image. required: - values type: object properties: values: description: An array of detected objects. type: array items: $ref: '#/definitions/DetectedObject' PeopleResult: description: An object describing whether the image contains people. required: - values type: object properties: values: description: An array of detected people. type: array items: $ref: '#/definitions/DetectedPerson' PlanogramApiModel: description: Describes the planogram for planogram matching operations. required: - fixtures - height - positions - products - width type: object properties: width: format: double description: Width of the planogram. type: number height: format: double description: Height of the planogram. type: number products: description: List of products in the planogram. minItems: 1 type: array items: $ref: '#/definitions/ProductApiModel' fixtures: description: List of fixtures in the planogram. minItems: 1 type: array items: $ref: '#/definitions/FixtureApiModel' positions: description: List of positions in the planogram. minItems: 1 type: array items: $ref: '#/definitions/PositionApiModel' PlanogramMatchingRequestApiModel: description: Input to pass into the planogram matching operation. required: - detectedProducts - planogram type: object properties: detectedProducts: $ref: '#/definitions/ProductRecognitionResultApiModel' planogram: $ref: '#/definitions/PlanogramApiModel' PlanogramMatchingResultApiModel: description: Results from the planogram matching operation. required: - matchingResultPerPosition type: object properties: matchingResultPerPosition: description: The matched detected object information for each planogram position. type: array items: $ref: '#/definitions/PositionMatchingResultApiModel' PositionApiModel: description: Describes a product position in a planogram. required: - fixtureId - id - productId - x - 'y' type: object properties: id: description: Id of the position. minLength: 1 type: string productId: description: Id of the product. minLength: 1 type: string fixtureId: description: Id of the fixture that the product is on. minLength: 1 type: string x: format: double description: Left offset from the origin, in unit of in inches or centimeters. minimum: 0 type: number 'y': format: double description: Top offset from the origin, in unit of in inches or centimeters. minimum: 0 type: number PositionMatchingResultApiModel: description: >- Paired planogram position ID and corresponding detected object from product understanding result. required: - detectedObject - positionId type: object properties: positionId: description: >- The position ID from the planogram matched to the corresponding detected object. minLength: 1 type: string detectedObject: $ref: '#/definitions/DetectedObject' ProductApiModel: description: Describes a product in the planogram. required: - h - id - name - w type: object properties: id: description: Id of the product. minLength: 1 type: string name: description: Name of the product. maxLength: 255 minLength: 1 type: string w: format: double description: Width of the product. type: number h: format: double description: Height of the fixture. type: number ProductRecognitionApiModel: required: - createdDateTime - modelName - result - runName - status - updatedDateTime type: object properties: runName: description: >- Read only. The name that is used to uniquely identify the product recognition run. maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ type: string modelName: description: Read only. The model to run product recognition against. maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ type: string createdDateTime: format: date-time description: >- Read only. The date and time when the product recognition run was first created, in UTC. type: string updatedDateTime: format: date-time description: >- Read only. The date and time when the product recognition run was last updated, in UTC. type: string status: description: Read only. The current state of the product recognition run. enum: - notStarted - running - succeeded - failed type: string x-ms-enum: name: ProductRecognitionState modelAsString: true error: $ref: '#/definitions/ErrorResponseDetails' result: $ref: '#/definitions/ProductRecognitionResultApiModel' ProductRecognitionApiModelCollectionApiModel: description: Contains an array of results that may be paginated. required: - value type: object properties: value: description: The array of results. type: array items: $ref: '#/definitions/ProductRecognitionApiModel' nextLink: description: >- A link to the next set of paginated results, if there are more results available; not present otherwise. type: string ProductRecognitionResultApiModel: description: Results from the product understanding operation. required: - gaps - imageMetadata - products type: object properties: imageMetadata: $ref: '#/definitions/ImageMetadataApiModel' products: description: Products detected in the image. type: array items: $ref: '#/definitions/DetectedObject' gaps: description: Gaps detected in the image. type: array items: $ref: '#/definitions/DetectedObject' ReadResult: description: The results of an Read operation. required: - content - pages - stringIndexType type: object properties: stringIndexType: description: >- The method used to compute string offset and length, possible values include: 'textElements', 'unicodeCodePoint', 'utf16CodeUnit' etc. minLength: 1 type: string content: description: >- Concatenate string representation of all textual and visual elements in reading order. minLength: 1 type: string pages: description: A list of analyzed pages. type: array items: $ref: '#/definitions/DocumentPage' styles: description: Extracted font styles. type: array items: $ref: '#/definitions/DocumentStyle' SingleVectorResultApiModel: description: Results of image vectorization. type: object properties: vector: description: Vector of the image. type: array items: format: float type: number modelVersion: description: Model version. type: string SmartCropsResult: description: Smart cropping result. required: - values type: object properties: values: description: Recommended regions for cropping the image. type: array items: $ref: '#/definitions/CropRegion' Tag: description: An entity observation in the image, along with the confidence score. required: - confidence - name type: object properties: name: description: Name of the entity. minLength: 1 type: string confidence: format: double description: The level of confidence that the entity was observed. maximum: 1 minimum: 0 type: number TagsResult: description: A list of tags with confidence level. required: - values type: object properties: values: description: A list of tags with confidence level. type: array items: $ref: '#/definitions/Tag' VectorizeTextRequestApiModel: description: Model for VectorizeText request. required: - text type: object properties: text: description: Text for vectorization. minLength: 1 type: string Dataset: description: >- Describes a dataset, which represents a set of images and annotations that can be used for training or testing a model. type: object properties: annotationKind: description: "The kind of annotations contained in the annotation files.\r\nFor example, \"ImageClassification\" to specify that the annotation file contain object labels for training or testing a multiclass image classification model." enum: - imageClassification - imageObjectDetection type: string x-ms-enum: name: AnnotationKind modelAsString: true annotationFileUris: description: "List of absolute URIs to annotation files, each of which must be stored as a blob in an Azure Storage blob container.\r\nEach file must follow the COCO format for the specified AnnotationKind, with each image path being an absolute URI to a blob in a blob container.\r\nThe Computer Vision resource must have permission to read the annotation files and all referenced image files.\r\nThis can be done by turning on System managed identities for the Computer Vision resource, then assigning the identity to a role that has permission to read from the blob container containing the annotation and image files." maxItems: 10 type: array items: format: uri type: string customProperties: description: >- Dictionary of arbitrary key-value pairs for use by the application. A maximum of 10 key-value pairs are allowed. maxLength: 10 type: object additionalProperties: type: string name: description: Read only. The name that is used to uniquely identify the dataset. maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ type: string createdDateTime: format: date-time description: >- Read only. The date and time when the dataset was first registered, in UTC. type: string updatedDateTime: format: date-time description: >- Read only. The date and time when the dataset was last updated, in UTC. type: string eTag: description: >- Read only. The latest ETag for the dataset. May be used with the 'If-Match' header when updating or deleting a dataset. type: string authentication: $ref: '#/definitions/StorageAuthenticationSettingsApiModel' DatasetApiModelCollectionApiModel: description: Contains an array of results that may be paginated. required: - value type: object properties: value: description: The array of results. type: array items: $ref: '#/definitions/Dataset' nextLink: description: >- A link to the next set of paginated results, if there are more results available; not present otherwise. type: string Model: description: Describes a training run for training a custom model. required: - trainingParameters type: object properties: trainingParameters: $ref: '#/definitions/TrainingParameters' name: description: >- Read only. The name that is used to uniquely identify the training run. maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ type: string createdDateTime: format: date-time description: >- Read only. The date and time when the training run was first created, in UTC. type: string updatedDateTime: format: date-time description: >- Read only. The date and time when the training run was last updated, in UTC. type: string status: description: Read only. The current state of the training run. enum: - notStarted - training - succeeded - failed - cancelling - cancelled type: string x-ms-enum: name: ModelState modelAsString: true trainingCostInMinutes: format: int32 description: >- Read only. Actual training cost consumed, in minutes. Present only if the training run as completed. type: integer readOnly: true error: $ref: '#/definitions/ErrorResponseDetails' modelPerformance: $ref: '#/definitions/ModelPerformance' evaluationParameters: $ref: '#/definitions/ModelEvaluationParameters' ModelApiModelCollectionApiModel: description: Contains an array of results that may be paginated. required: - value type: object properties: value: description: The array of results. type: array items: $ref: '#/definitions/Model' nextLink: description: >- A link to the next set of paginated results, if there are more results available; not present otherwise. type: string ModelEvaluation: description: >- Describes an evaluation run for evaluating the accuracy of a model using a test set. required: - evaluationParameters type: object properties: name: description: >- Read only. The name that is used to uniquely identify the evaluation run. maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ type: string modelName: description: Read only. The model to evaluate. maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ type: string createdDateTime: format: date-time description: >- Read only. The date and time when the evaluation run was first created, in UTC. type: string updatedDateTime: format: date-time description: >- Read only. The date and time when the evaluation run was last updated, in UTC. type: string status: description: Read only. The current state of the evaluation run. enum: - notStarted - running - succeeded - failed type: string x-ms-enum: name: ModelEvaluationState modelAsString: true evaluationParameters: $ref: '#/definitions/ModelEvaluationParameters' error: $ref: '#/definitions/ErrorResponseDetails' modelPerformance: $ref: '#/definitions/ModelPerformance' ModelEvaluationApiModelCollectionApiModel: description: Contains an array of results that may be paginated. required: - value type: object properties: value: description: The array of results. type: array items: $ref: '#/definitions/ModelEvaluation' nextLink: description: >- A link to the next set of paginated results, if there are more results available; not present otherwise. type: string ModelEvaluationParameters: description: Parameters for specifying how a model is evaluated. type: object properties: testDatasetName: description: The dataset name used for testing. maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ type: string ModelPerformance: description: Performance metrics for a custom trained model. required: - tagPerformance type: object properties: accuracyTop1: format: double description: >- Read only. For multiclass classification models. The proportion of test samples where the ground truth class matches the predicted class. type: number readOnly: true accuracyTop5: format: double description: >- Read only. For multiclass classification models. The proportion of test samples where the ground truth class is in the top five predicted classes. type: number readOnly: true averagePrecision: format: double description: >- Read only. A measure of the model performance, it summarizes the precision and recall at different confidence thresholds. type: number readOnly: true calibrationECE: format: double description: >- Read only. For multiclass classification models. Expected calibration error. type: number readOnly: true meanAveragePrecision30: format: double description: >- Read only. For object detection models. Mean average precision at a threshold of 30%. type: number readOnly: true meanAveragePrecision50: format: double description: >- Read only. For object detection models. Mean average precision at a threshold of 50%. type: number readOnly: true meanAveragePrecision75: format: double description: >- Read only. For object detection models. Mean average precision at a threshold of 75%. type: number readOnly: true tagPerformance: description: Read only. Performance metrics for each tag recognized by the model. type: object additionalProperties: $ref: '#/definitions/ModelTagPerformance' ModelTagPerformance: description: Performance metrics for each tag recognized by a custom trained model. type: object properties: accuracy: format: double description: Read only. For multiclass models. Tag accuracy. type: number readOnly: true averagePrecision50: format: double description: >- Read only. For object detection models. Average precision at a threshold of 50%. type: number readOnly: true StorageAuthenticationSettingsApiModel: description: Describes the storage authentication settings. required: - kind type: object properties: kind: description: The storage authentication kind. enum: - none - managedIdentity - sas type: string x-ms-enum: name: StorageAuthenticationKind modelAsString: true sasToken: description: >- Optional. The sas token to access container. Only needed when Kind = Sas. type: string TrainingParameters: description: Parameters for specifying how a training run trains a custom model. required: - timeBudgetInHours - trainingDatasetName type: object properties: trainingDatasetName: description: The dataset name used for training. maxLength: 255 pattern: ^[a-zA-Z0-9][a-zA-Z0-9._-]*$ type: string timeBudgetInHours: format: int32 description: "Time budget for training, in hours. The minimum allowed value is 1, and the maximum allowed value is 336 hours for GenericClassifier, 1344 hours for GenericDetector.\r\nThis is the maximum amount of compute time that will be spent to train the model." maximum: 1344 minimum: 1 type: integer modelKind: description: Model kind. enum: - Product-Recognizer - Generic-Classifier - Generic-Detector type: string x-ms-enum: name: ModelKind modelAsString: true parameters: ApiVersion: in: query name: api-version description: Requested API version. required: true type: string x-ms-parameter-location: client x-ms-paths: /imageanalysis:segment?overload=stream: post: tags: - Operations summary: >- Analyze the input image. The request either contains an image stream with any content type ['image/*', 'application/octet-stream'], or a JSON payload which includes a url property to be used to retrieve the image stream. An image stream of content type 'image/png' is returned, where the pixel values depend on the analysis mode. The returned image has the same dimensions as the input image for modes: foregroundMatting. The returned image has the same aspect ratio and same dimensions as the input image up to a limit of 16 megapixels for modes: backgroundRemoval. operationId: ImageAnalysis_SegmentFromImageStream consumes: - application/octet-stream - image/jpeg - image/gif - image/tiff - image/bmp - image/png produces: - image/png - application/json parameters: - in: query name: mode description: The analysis mode requested. type: string enum: - backgroundRemoval - foregroundMatting x-ms-enum: name: SegmentationMode modelAsString: true - $ref: '#/parameters/ApiVersion' - in: body name: body description: An image stream. required: true schema: format: byte type: string responses: '200': description: Success schema: type: file default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: Segment_BackgroundRemoval_FromImageStream: $ref: ./examples/Segment_BackgroundRemoval_FromImageStream.json Segment_ForegroundMatting_FromImageStream: $ref: ./examples/Segment_ForegroundMatting_FromImageStream.json /retrieval:vectorizeImage?overload=stream: post: tags: - ImageRetrieval summary: Return vector from an image. operationId: ImageRetrieval_VectorizeImageFromImageStream consumes: - application/octet-stream - image/jpeg - image/gif - image/tiff - image/bmp - image/png produces: - application/json parameters: - in: query name: model-version description: Model version. type: string - $ref: '#/parameters/ApiVersion' - in: body name: body description: An image stream. required: true schema: format: byte type: string responses: '200': description: Success schema: $ref: '#/definitions/SingleVectorResultApiModel' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: ImageRetrieval_VectorizeImageFromImageStream: $ref: ./examples/ImageRetrieval_VectorizeImageFromImageStream.json /imageanalysis:analyze?overload=stream: post: tags: - Operations summary: >- Analyze the input image. The request either contains image stream with any content type ['image/*', 'application/octet-stream'], or a JSON payload which includes an url property to be used to retrieve the image stream. operationId: ImageAnalysis_AnalyzeFromImageStream consumes: - application/octet-stream - image/jpeg - image/gif - image/tiff - image/bmp - image/png produces: - application/json parameters: - in: query name: features description: >- The visual features requested: tags, objects, caption, denseCaptions, read, smartCrops, people. This parameter needs to be specified if the parameter "model-name" is not specified. type: array items: enum: - tags - caption - denseCaptions - objects - read - smartCrops - people type: string x-ms-enum: name: VisualFeature modelAsString: true collectionFormat: csv - in: query name: model-name description: >- The name of the custom trained model. This parameter needs to be specified if the parameter "features" is not specified. type: string - in: query name: language description: >- The desired language for output generation. If this parameter is not specified, the default value is "en". See https://aka.ms/cv-languages for a list of supported languages. type: string default: en - in: query name: smartcrops-aspect-ratios description: >- A list of aspect ratios to use for smartCrops feature. Aspect ratios are calculated by dividing the target crop width by the height. Supported values are between 0.75 and 1.8 (inclusive). Multiple values should be comma-separated. If this parameter is not specified, the service will return one crop suggestion with an aspect ratio it sees fit between 0.5 and 2.0 (inclusive). type: string - in: query name: gender-neutral-caption description: >- Boolean flag for enabling gender-neutral captioning for caption and denseCaptions features. If this parameter is not specified, the default value is "false". type: boolean default: false - $ref: '#/parameters/ApiVersion' - in: body name: body description: An image stream. required: true schema: format: byte type: string responses: '200': description: Success schema: $ref: '#/definitions/ImageAnalysisResult' default: description: Error schema: $ref: '#/definitions/ErrorResponse' headers: x-ms-error-code: type: string x-ms-examples: AnalyzeImageFromImageStream_CustomModel: $ref: ./examples/AnalyzeImageFromImageStream_CustomModel.json tags: - name: Datasets - name: ImageRetrieval - name: Models - name: Operations