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Types for Google Cloud Aiplatform V1beta1 Schema Predict Instance v1beta1 API

class google.cloud.aiplatform.v1beta1.schema.predict.instance_v1beta1.types.ImageClassificationPredictionInstance(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Prediction input format for Image Classification.

content()

The image bytes or Cloud Storage URI to make the prediction on.

• Type

  str

mime_type()

The MIME type of the content of the image. Only the images in below listed MIME types are supported.

• image/jpeg
• image/gif
• image/png
• image/webp
• image/bmp
• image/tiff

• image/vnd.microsoft.icon

• Type

  str

content(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

mime_type(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

class google.cloud.aiplatform.v1beta1.schema.predict.instance_v1beta1.types.ImageObjectDetectionPredictionInstance(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Prediction input format for Image Object Detection.

content()

The image bytes or Cloud Storage URI to make the prediction on.

• Type

  str

mime_type()

The MIME type of the content of the image. Only the images in below listed MIME types are supported.

• image/jpeg
• image/gif
• image/png
• image/webp
• image/bmp
• image/tiff

• image/vnd.microsoft.icon

• Type

  str

content(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

mime_type(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

class google.cloud.aiplatform.v1beta1.schema.predict.instance_v1beta1.types.ImageSegmentationPredictionInstance(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Prediction input format for Image Segmentation.

content()

The image bytes to make the predictions on.

• Type

  str

mime_type()

The MIME type of the content of the image. Only the images in below listed MIME types are supported.

• image/jpeg

• image/png

• Type

  str

content(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

mime_type(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

class google.cloud.aiplatform.v1beta1.schema.predict.instance_v1beta1.types.TextClassificationPredictionInstance(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Prediction input format for Text Classification.

content()

The text snippet to make the predictions on.

• Type

  str

mime_type()

The MIME type of the text snippet. The supported MIME types are listed below.

• text/plain

• Type

  str

content(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

mime_type(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

class google.cloud.aiplatform.v1beta1.schema.predict.instance_v1beta1.types.TextExtractionPredictionInstance(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Prediction input format for Text Extraction.

content()

The text snippet to make the predictions on.

• Type

  str

mime_type()

The MIME type of the text snippet. The supported MIME types are listed below.

• text/plain

• Type

  str

key()

This field is only used for batch prediction. If a key is provided, the batch prediction result will by mapped to this key. If omitted, then the batch prediction result will contain the entire input instance. Vertex AI will not check if keys in the request are duplicates, so it is up to the caller to ensure the keys are unique.

• Type

  str

content(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

key(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

mime_type(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

class google.cloud.aiplatform.v1beta1.schema.predict.instance_v1beta1.types.TextSentimentPredictionInstance(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Prediction input format for Text Sentiment.

content()

The text snippet to make the predictions on.

• Type

  str

mime_type()

The MIME type of the text snippet. The supported MIME types are listed below.

• text/plain

• Type

  str

content(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

mime_type(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

class google.cloud.aiplatform.v1beta1.schema.predict.instance_v1beta1.types.VideoActionRecognitionPredictionInstance(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Prediction input format for Video Action Recognition.

content()

The Google Cloud Storage location of the video on which to perform the prediction.

• Type

  str

mime_type()

The MIME type of the content of the video. Only the following are supported: video/mp4 video/avi video/quicktime

• Type

  str

time_segment_start()

The beginning, inclusive, of the video’s time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with “s” appended at the end. Fractions are allowed, up to a microsecond precision.

• Type

  str

time_segment_end()

The end, exclusive, of the video’s time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with “s” appended at the end. Fractions are allowed, up to a microsecond precision, and “inf” or “Infinity” is allowed, which means the end of the video.

• Type

  str

content(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

mime_type(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

time_segment_end(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

time_segment_start(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

class google.cloud.aiplatform.v1beta1.schema.predict.instance_v1beta1.types.VideoClassificationPredictionInstance(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Prediction input format for Video Classification.

content()

The Google Cloud Storage location of the video on which to perform the prediction.

• Type

  str

mime_type()

The MIME type of the content of the video. Only the following are supported: video/mp4 video/avi video/quicktime

• Type

  str

time_segment_start()

The beginning, inclusive, of the video’s time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with “s” appended at the end. Fractions are allowed, up to a microsecond precision.

• Type

  str

time_segment_end()

The end, exclusive, of the video’s time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with “s” appended at the end. Fractions are allowed, up to a microsecond precision, and “inf” or “Infinity” is allowed, which means the end of the video.

• Type

  str

content(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

mime_type(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

time_segment_end(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

time_segment_start(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

class google.cloud.aiplatform.v1beta1.schema.predict.instance_v1beta1.types.VideoObjectTrackingPredictionInstance(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Bases: proto.message.Message

Prediction input format for Video Object Tracking.

content()

The Google Cloud Storage location of the video on which to perform the prediction.

• Type

  str

mime_type()

The MIME type of the content of the video. Only the following are supported: video/mp4 video/avi video/quicktime

• Type

  str

time_segment_start()

The beginning, inclusive, of the video’s time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with “s” appended at the end. Fractions are allowed, up to a microsecond precision.

• Type

  str

time_segment_end()

The end, exclusive, of the video’s time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with “s” appended at the end. Fractions are allowed, up to a microsecond precision, and “inf” or “Infinity” is allowed, which means the end of the video.

• Type

  str

content(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

mime_type(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

time_segment_end(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )

time_segment_start(: [str](https://python.readthedocs.io/en/latest/library/stdtypes.html#str )