apache_beam.ml.gcp.videointelligenceml module¶

A connector for sending API requests to the GCP Video Intelligence API.

class apache_beam.ml.gcp.videointelligenceml.AnnotateVideo(features, location_id=None, metadata=None, timeout=120, context_side_input=None)[source]¶

Bases: apache_beam.transforms.ptransform.PTransform

A PTransform for annotating video using the GCP Video Intelligence API ref: https://cloud.google.com/video-intelligence/docs

Sends each element to the GCP Video Intelligence API. Element is a Union[text_type, binary_type] of either an URI (e.g. a GCS URI) or binary_type base64-encoded video data. Accepts an AsDict side input that maps each video to a video context.

Parameters:

features – (List[videointelligence_v1.enums.Feature]) Required. The Video Intelligence API features to detect
location_id – (str) Optional. Cloud region where annotation should take place. If no region is specified, a region will be determined based on video file location.
metadata – (Sequence[Tuple[str, str]]) Optional. Additional metadata that is provided to the method.
timeout – (int) Optional. The time in seconds to wait for the response from the Video Intelligence API

context_side_input –

(beam.pvalue.AsDict) Optional. An AsDict of a PCollection to be passed to the _VideoAnnotateFn as the video context mapping containing additional video context and/or feature-specific parameters. Example usage:

video_contexts =
  [('gs://cloud-samples-data/video/cat.mp4', Union[dict,
  ``videointelligence_v1.types.VideoContext``]),
  ('gs://some-other-video/sample.mp4', Union[dict,
  ``videointelligence_v1.types.VideoContext``]),]

context_side_input =
  (
    p
    | "Video contexts" >> beam.Create(video_contexts)
  )

videointelligenceml.AnnotateVideo(features,
  context_side_input=beam.pvalue.AsDict(context_side_input)))

expand(pvalue)[source]¶

annotations() → Dict[str, Union[bytes, str, google.protobuf.message.Message]]¶

default_label()¶

default_type_hints()¶

display_data()¶

Returns the display data associated to a pipeline component.

It should be reimplemented in pipeline components that wish to have static display data.

Returns:

A dictionary containing key:value pairs. The value might be an integer, float or string value; a DisplayDataItem for values that have more data (e.g. short value, label, url); or a HasDisplayData instance that has more display data that should be picked up. For example:

{
  'key1': 'string_value',
  'key2': 1234,
  'key3': 3.14159265,
  'key4': DisplayDataItem('apache.org', url='http://apache.org'),
  'key5': subComponent
}

Return type: Dict[str, Any]

classmethod from_runner_api(proto, context)¶

get_type_hints()¶

Gets and/or initializes type hints for this object.

If type hints have not been set, attempts to initialize type hints in this order: - Using self.default_type_hints(). - Using self.__class__ type hints.

get_windowing(inputs)¶

Returns the window function to be associated with transform’s output.

By default most transforms just return the windowing function associated with the input PCollection (or the first input if several).

infer_output_type(unused_input_type)¶

label¶

pipeline = None¶

classmethod register_urn(urn, parameter_type, constructor=None)¶

runner_api_requires_keyed_input()¶

side_inputs = ()¶

to_runner_api(context, has_parts=False, **extra_kwargs)¶

to_runner_api_parameter(unused_context)¶

to_runner_api_pickled(unused_context)¶

type_check_inputs(pvalueish)¶

type_check_inputs_or_outputs(pvalueish, input_or_output)¶

type_check_outputs(pvalueish)¶

with_input_types(input_type_hint)¶

Annotates the input type of a PTransform with a type-hint.

Parameters:	input_type_hint (type) – An instance of an allowed built-in type, a custom class, or an instance of a `TypeConstraint`.
Raises:	`TypeError` – If input_type_hint is not a valid type-hint. See `apache_beam.typehints.typehints.validate_composite_type_param()` for further details.
Returns:	A reference to the instance of this particular `PTransform` object. This allows chaining type-hinting related methods.
Return type:	PTransform

with_output_types(type_hint)¶

Annotates the output type of a PTransform with a type-hint.

Parameters:	type_hint (type) – An instance of an allowed built-in type, a custom class, or a `TypeConstraint`.
Raises:	`TypeError` – If type_hint is not a valid type-hint. See `validate_composite_type_param()` for further details.
Returns:	A reference to the instance of this particular `PTransform` object. This allows chaining type-hinting related methods.
Return type:	PTransform

class apache_beam.ml.gcp.videointelligenceml.AnnotateVideoWithContext(features, location_id=None, metadata=None, timeout=120)[source]¶

Bases: apache_beam.ml.gcp.videointelligenceml.AnnotateVideo