BatchPredictRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)Request message for PredictionService.BatchPredict.
Attributes
| Name | Description |
name |
str
Required. Name of the model requested to serve the batch prediction. |
input_config |
Required. The input configuration for batch prediction. |
output_config |
Required. The Configuration specifying where output predictions should be written. |
params |
Sequence[
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.
|
Classes
ParamsEntry
ParamsEntry(mapping=None, *, ignore_unknown_fields=False, **kwargs)The abstract base class for a message.
| 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 |