public sealed class ImageObjectDetectionModelMetadata : IMessage<ImageObjectDetectionModelMetadata>, IEquatable<ImageObjectDetectionModelMetadata>, IDeepCloneable<ImageObjectDetectionModelMetadata>, IBufferMessage, IMessage
Reference documentation and code samples for the Google AutoML v1 API class ImageObjectDetectionModelMetadata.
Model metadata specific to image object detection.
Implements
IMessage<ImageObjectDetectionModelMetadata>, IEquatable<ImageObjectDetectionModelMetadata>, IDeepCloneable<ImageObjectDetectionModelMetadata>, IBufferMessage, IMessageNamespace
Google.Cloud.AutoML.V1Assembly
Google.Cloud.AutoML.V1.dll
Constructors
ImageObjectDetectionModelMetadata()
public ImageObjectDetectionModelMetadata()
ImageObjectDetectionModelMetadata(ImageObjectDetectionModelMetadata)
public ImageObjectDetectionModelMetadata(ImageObjectDetectionModelMetadata other)
Parameter | |
---|---|
Name | Description |
other | ImageObjectDetectionModelMetadata |
Properties
ModelType
public string ModelType { get; set; }
Optional. Type of the model. The available values are:
cloud-high-accuracy-1
- (default) A model to be used via prediction calls to AutoML API. Expected to have a higher latency, but should also have a higher prediction quality than other models.cloud-low-latency-1
- A model to be used via prediction calls to AutoML API. Expected to have low latency, but may have lower prediction quality than other models.mobile-low-latency-1
- A model that, in addition to providing prediction via AutoML API, can also be exported (see [AutoMl.ExportModel][google.cloud.automl.v1.AutoMl.ExportModel]) and used on a mobile or edge device with TensorFlow afterwards. Expected to have low latency, but may have lower prediction quality than other models.mobile-versatile-1
- A model that, in addition to providing prediction via AutoML API, can also be exported (see [AutoMl.ExportModel][google.cloud.automl.v1.AutoMl.ExportModel]) and used on a mobile or edge device with TensorFlow afterwards.mobile-high-accuracy-1
- A model that, in addition to providing prediction via AutoML API, can also be exported (see [AutoMl.ExportModel][google.cloud.automl.v1.AutoMl.ExportModel]) and used on a mobile or edge device with TensorFlow afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other models.
Property Value | |
---|---|
Type | Description |
String |
NodeCount
public long NodeCount { get; set; }
Output only. The number of nodes this model is deployed on. A node is an abstraction of a machine resource, which can handle online prediction QPS as given in the qps_per_node field.
Property Value | |
---|---|
Type | Description |
Int64 |
NodeQps
public double NodeQps { get; set; }
Output only. An approximate number of online prediction QPS that can be supported by this model per each node on which it is deployed.
Property Value | |
---|---|
Type | Description |
Double |
StopReason
public string StopReason { get; set; }
Output only. The reason that this create model operation stopped,
e.g. BUDGET_REACHED
, MODEL_CONVERGED
.
Property Value | |
---|---|
Type | Description |
String |
TrainBudgetMilliNodeHours
public long TrainBudgetMilliNodeHours { get; set; }
Optional. The train budget of creating this model, expressed in milli node
hours i.e. 1,000 value in this field means 1 node hour. The actual
train_cost
will be equal or less than this value. If further model
training ceases to provide any improvements, it will stop without using
full budget and the stop_reason will be MODEL_CONVERGED
.
Note, node_hour = actual_hour * number_of_nodes_invovled.
For model type cloud-high-accuracy-1
(default) and cloud-low-latency-1
,
the train budget must be between 20,000 and 900,000 milli node hours,
inclusive. The default value is 216, 000 which represents one day in
wall time.
For model type mobile-low-latency-1
, mobile-versatile-1
,
mobile-high-accuracy-1
, mobile-core-ml-low-latency-1
,
mobile-core-ml-versatile-1
, mobile-core-ml-high-accuracy-1
, the train
budget must be between 1,000 and 100,000 milli node hours, inclusive.
The default value is 24, 000 which represents one day in wall time.
Property Value | |
---|---|
Type | Description |
Int64 |
TrainCostMilliNodeHours
public long TrainCostMilliNodeHours { get; set; }
Output only. The actual train cost of creating this model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget.
Property Value | |
---|---|
Type | Description |
Int64 |