Cloud AutoML V1beta1 API - Class Google::Cloud::AutoML::V1beta1::BatchPredictRequest (v0.7.0)

Reference documentation and code samples for the Cloud AutoML V1beta1 API class Google::Cloud::AutoML::V1beta1::BatchPredictRequest.

Request message for PredictionService.BatchPredict.

Inherits

Object

Extended By

Google::Protobuf::MessageExts::ClassMethods

Includes

Google::Protobuf::MessageExts

Methods

#input_config

def input_config() -> ::Google::Cloud::AutoML::V1beta1::BatchPredictInputConfig

Returns

(::Google::Cloud::AutoML::V1beta1::BatchPredictInputConfig) — Required. The input configuration for batch prediction.

#input_config=

def input_config=(value) -> ::Google::Cloud::AutoML::V1beta1::BatchPredictInputConfig

Parameter

value (::Google::Cloud::AutoML::V1beta1::BatchPredictInputConfig) — Required. The input configuration for batch prediction.

Returns

(::Google::Cloud::AutoML::V1beta1::BatchPredictInputConfig) — Required. The input configuration for batch prediction.

#name

def name() -> ::String

Returns

(::String) — Required. Name of the model requested to serve the batch prediction.

#name=

def name=(value) -> ::String

Parameter

value (::String) — Required. Name of the model requested to serve the batch prediction.

Returns

(::String) — Required. Name of the model requested to serve the batch prediction.

#output_config

def output_config() -> ::Google::Cloud::AutoML::V1beta1::BatchPredictOutputConfig

Returns

(::Google::Cloud::AutoML::V1beta1::BatchPredictOutputConfig) — Required. The Configuration specifying where output predictions should be written.

#output_config=

def output_config=(value) -> ::Google::Cloud::AutoML::V1beta1::BatchPredictOutputConfig

Parameter

value (::Google::Cloud::AutoML::V1beta1::BatchPredictOutputConfig) — Required. The Configuration specifying where output predictions should be written.

Returns

(::Google::Cloud::AutoML::V1beta1::BatchPredictOutputConfig) — Required. The Configuration specifying where output predictions should be written.

#params

def params() -> ::Google::Protobuf::Map{::String => ::String}

Returns

(::Google::Protobuf::Map{::String => ::String}) — Required. Additional domain-specific parameters for the predictions, any string must be up to 25000 characters long.
- For Text Classification:
score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for a text snippet, it will only produce results that have at least this confidence score. The default is 0.5.
- For Image Classification:
score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for an image, it will only produce results that have at least this confidence score. The default is 0.5.
- For Image Object Detection:
score_threshold - (float) When Model detects objects on the image, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5. max_bounding_box_count - (int64) No more than this number of bounding boxes will be produced per image. Default is 100, the requested value may be limited by server.
- For Video Classification :
score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for a video, it will only produce results that have at least this confidence score. The default is 0.5. segment_classification - (boolean) Set to true to request segment-level classification. AutoML Video Intelligence returns labels and their confidence scores for the entire segment of the video that user specified in the request configuration. The default is "true". shot_classification - (boolean) Set to true to request shot-level classification. AutoML Video Intelligence determines the boundaries for each camera shot in the entire segment of the video that user specified in the request configuration. AutoML Video Intelligence then returns labels and their confidence scores for each detected shot, along with the start and end time of the shot. WARNING: Model evaluation is not done for this classification type, the quality of it depends on training data, but there are no metrics provided to describe that quality. The default is "false". 1s_interval_classification - (boolean) Set to true to request classification for a video at one-second intervals. AutoML Video Intelligence returns labels and their confidence scores for each second of the entire segment of the video that user specified in the request configuration. WARNING: Model evaluation is not done for this classification type, the quality of it depends on training data, but there are no metrics provided to describe that quality. The default is "false".
- For Tables:
feature_importance - (boolean) Whether feature importance should be populated in the returned TablesAnnotations. The default is false.
- For Video Object Tracking:
score_threshold - (float) When Model detects objects on video frames, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5. max_bounding_box_count - (int64) No more than this number of bounding boxes will be returned per frame. Default is 100, the requested value may be limited by server. min_bounding_box_size - (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size will be returned. Value in 0 to 1 range. Default is 0.

#params=

def params=(value) -> ::Google::Protobuf::Map{::String => ::String}

Parameter

value (::Google::Protobuf::Map{::String => ::String}) — Required. Additional domain-specific parameters for the predictions, any string must be up to 25000 characters long.
- For Text Classification:
score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for a text snippet, it will only produce results that have at least this confidence score. The default is 0.5.
- For Image Classification:
score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for an image, it will only produce results that have at least this confidence score. The default is 0.5.
- For Image Object Detection:
score_threshold - (float) When Model detects objects on the image, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5. max_bounding_box_count - (int64) No more than this number of bounding boxes will be produced per image. Default is 100, the requested value may be limited by server.
- For Video Classification :
score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for a video, it will only produce results that have at least this confidence score. The default is 0.5. segment_classification - (boolean) Set to true to request segment-level classification. AutoML Video Intelligence returns labels and their confidence scores for the entire segment of the video that user specified in the request configuration. The default is "true". shot_classification - (boolean) Set to true to request shot-level classification. AutoML Video Intelligence determines the boundaries for each camera shot in the entire segment of the video that user specified in the request configuration. AutoML Video Intelligence then returns labels and their confidence scores for each detected shot, along with the start and end time of the shot. WARNING: Model evaluation is not done for this classification type, the quality of it depends on training data, but there are no metrics provided to describe that quality. The default is "false". 1s_interval_classification - (boolean) Set to true to request classification for a video at one-second intervals. AutoML Video Intelligence returns labels and their confidence scores for each second of the entire segment of the video that user specified in the request configuration. WARNING: Model evaluation is not done for this classification type, the quality of it depends on training data, but there are no metrics provided to describe that quality. The default is "false".
- For Tables:
feature_importance - (boolean) Whether feature importance should be populated in the returned TablesAnnotations. The default is false.
- For Video Object Tracking:
score_threshold - (float) When Model detects objects on video frames, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5. max_bounding_box_count - (int64) No more than this number of bounding boxes will be returned per frame. Default is 100, the requested value may be limited by server. min_bounding_box_size - (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size will be returned. Value in 0 to 1 range. Default is 0.

Returns

(::Google::Protobuf::Map{::String => ::String}) — Required. Additional domain-specific parameters for the predictions, any string must be up to 25000 characters long.
- For Text Classification:
score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for a text snippet, it will only produce results that have at least this confidence score. The default is 0.5.
- For Image Classification:
score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for an image, it will only produce results that have at least this confidence score. The default is 0.5.
- For Image Object Detection:
score_threshold - (float) When Model detects objects on the image, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5. max_bounding_box_count - (int64) No more than this number of bounding boxes will be produced per image. Default is 100, the requested value may be limited by server.
- For Video Classification :
score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for a video, it will only produce results that have at least this confidence score. The default is 0.5. segment_classification - (boolean) Set to true to request segment-level classification. AutoML Video Intelligence returns labels and their confidence scores for the entire segment of the video that user specified in the request configuration. The default is "true". shot_classification - (boolean) Set to true to request shot-level classification. AutoML Video Intelligence determines the boundaries for each camera shot in the entire segment of the video that user specified in the request configuration. AutoML Video Intelligence then returns labels and their confidence scores for each detected shot, along with the start and end time of the shot. WARNING: Model evaluation is not done for this classification type, the quality of it depends on training data, but there are no metrics provided to describe that quality. The default is "false". 1s_interval_classification - (boolean) Set to true to request classification for a video at one-second intervals. AutoML Video Intelligence returns labels and their confidence scores for each second of the entire segment of the video that user specified in the request configuration. WARNING: Model evaluation is not done for this classification type, the quality of it depends on training data, but there are no metrics provided to describe that quality. The default is "false".
- For Tables:
feature_importance - (boolean) Whether feature importance should be populated in the returned TablesAnnotations. The default is false.
- For Video Object Tracking:
score_threshold - (float) When Model detects objects on video frames, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5. max_bounding_box_count - (int64) No more than this number of bounding boxes will be returned per frame. Default is 100, the requested value may be limited by server. min_bounding_box_size - (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size will be returned. Value in 0 to 1 range. Default is 0.