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Types for Google Cloud Aiplatform V1 Schema Predict Params v1 API
class google.cloud.aiplatform.v1.schema.predict.params_v1.types.ImageClassificationPredictionParams(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Bases: proto.message.Message
Prediction model parameters for Image Classification.
confidence_threshold()
The Model only returns predictions with at least this confidence score. Default value is 0.0
Type
max_predictions()
The Model only returns up to that many top, by confidence score, predictions per instance. If this number is very high, the Model may return fewer predictions. Default value is 10.
Type
confidence_threshold(: [float](https://python.readthedocs.io/en/latest/library/functions.html#float )
max_predictions(: [int](https://python.readthedocs.io/en/latest/library/functions.html#int )
class google.cloud.aiplatform.v1.schema.predict.params_v1.types.ImageObjectDetectionPredictionParams(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Bases: proto.message.Message
Prediction model parameters for Image Object Detection.
confidence_threshold()
The Model only returns predictions with at least this confidence score. Default value is 0.0
Type
max_predictions()
The Model only returns up to that many top, by confidence score, predictions per instance. Note that number of returned predictions is also limited by metadata’s predictionsLimit. Default value is 10.
Type
confidence_threshold(: [float](https://python.readthedocs.io/en/latest/library/functions.html#float )
max_predictions(: [int](https://python.readthedocs.io/en/latest/library/functions.html#int )
class google.cloud.aiplatform.v1.schema.predict.params_v1.types.ImageSegmentationPredictionParams(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Bases: proto.message.Message
Prediction model parameters for Image Segmentation.
confidence_threshold()
When the model predicts category of pixels of the image, it will only provide predictions for pixels that it is at least this much confident about. All other pixels will be classified as background. Default value is 0.5.
Type
confidence_threshold(: [float](https://python.readthedocs.io/en/latest/library/functions.html#float )
class google.cloud.aiplatform.v1.schema.predict.params_v1.types.VideoActionRecognitionPredictionParams(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Bases: proto.message.Message
Prediction model parameters for Video Action Recognition.
confidence_threshold()
The Model only returns predictions with at least this confidence score. Default value is 0.0
Type
max_predictions()
The model only returns up to that many top, by confidence score, predictions per frame of the video. If this number is very high, the Model may return fewer predictions per frame. Default value is 50.
Type
confidence_threshold(: [float](https://python.readthedocs.io/en/latest/library/functions.html#float )
max_predictions(: [int](https://python.readthedocs.io/en/latest/library/functions.html#int )
class google.cloud.aiplatform.v1.schema.predict.params_v1.types.VideoClassificationPredictionParams(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Bases: proto.message.Message
Prediction model parameters for Video Classification.
confidence_threshold()
The Model only returns predictions with at least this confidence score. Default value is 0.0
Type
max_predictions()
The Model only returns up to that many top, by confidence score, predictions per instance. If this number is very high, the Model may return fewer predictions. Default value is 10,000.
Type
segment_classification()
Set to true to request segment-level classification. Vertex AI returns labels and their confidence scores for the entire time segment of the video that user specified in the input instance. Default value is true
Type
shot_classification()
Set to true to request shot-level classification. Vertex AI determines the boundaries for each camera shot in the entire time segment of the video that user specified in the input instance. Vertex AI 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 the training data, but there are no metrics provided to describe that quality. Default value is false
Type
one_sec_interval_classification()
Set to true to request classification for a video at one-second intervals. Vertex AI returns labels and their confidence scores for each second of the entire time segment of the video that user specified in the input WARNING: Model evaluation is not done for this classification type, the quality of it depends on the training data, but there are no metrics provided to describe that quality. Default value is false
Type
confidence_threshold(: [float](https://python.readthedocs.io/en/latest/library/functions.html#float )
max_predictions(: [int](https://python.readthedocs.io/en/latest/library/functions.html#int )
one_sec_interval_classification(: [bool](https://python.readthedocs.io/en/latest/library/functions.html#bool )
segment_classification(: [bool](https://python.readthedocs.io/en/latest/library/functions.html#bool )
shot_classification(: [bool](https://python.readthedocs.io/en/latest/library/functions.html#bool )
class google.cloud.aiplatform.v1.schema.predict.params_v1.types.VideoObjectTrackingPredictionParams(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Bases: proto.message.Message
Prediction model parameters for Video Object Tracking.
confidence_threshold()
The Model only returns predictions with at least this confidence score. Default value is 0.0
Type
max_predictions()
The model only returns up to that many top, by confidence score, predictions per frame of the video. If this number is very high, the Model may return fewer predictions per frame. Default value is 50.
Type
min_bounding_box_size()
Only bounding boxes with shortest edge at least that long as a relative value of video frame size are returned. Default value is 0.0.
Type