BatchPredictRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Request message for PredictionService.BatchPredict.
Attributes |
|
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Name | Description |
name |
str
Required. Name of the model requested to serve the batch prediction. |
input_config |
google.cloud.automl_v1.types.BatchPredictInputConfig
Required. The input configuration for batch prediction. |
output_config |
google.cloud.automl_v1.types.BatchPredictOutputConfig
Required. The Configuration specifying where output predictions should be written. |
params |
MutableMapping[str, str]
Additional domain-specific parameters for the predictions, any string must be up to 25000 characters long. AutoML Natural Language 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.
AutoML Vision 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.
AutoML Vision 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) The maximum number of
bounding boxes returned per image. The default is 100, the
number of bounding boxes returned might be limited by the
server. AutoML Video Intelligence 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. The default is
false.
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.
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.
The default is false.
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.
AutoML Video Intelligence 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) The maximum number of
bounding boxes returned per image. The default is 100, the
number of bounding boxes returned might be limited by the
server.
min_bounding_box_size : (float) Only bounding boxes with
shortest edge at least that long as a relative value of
video frame size are returned. Value in 0 to 1 range.
Default is 0.
|
Classes
ParamsEntry
ParamsEntry(mapping=None, *, ignore_unknown_fields=False, **kwargs)
The abstract base class for a message.
Parameters | |
---|---|
Name | Description |
kwargs |
dict
Keys and values corresponding to the fields of the message. |
mapping |
Union[dict,
A dictionary or message to be used to determine the values for this message. |
ignore_unknown_fields |
Optional(bool)
If True, do not raise errors for unknown fields. Only applied if |