Model¶

class oci.ai_vision.models.Model(**kwargs)¶

Bases: object

Machine-learned Model.

Attributes

`LIFECYCLE_STATE_ACTIVE`	A constant which can be used with the lifecycle_state property of a Model.
`LIFECYCLE_STATE_CREATING`	A constant which can be used with the lifecycle_state property of a Model.
`LIFECYCLE_STATE_DELETED`	A constant which can be used with the lifecycle_state property of a Model.
`LIFECYCLE_STATE_DELETING`	A constant which can be used with the lifecycle_state property of a Model.
`LIFECYCLE_STATE_FAILED`	A constant which can be used with the lifecycle_state property of a Model.
`LIFECYCLE_STATE_UPDATING`	A constant which can be used with the lifecycle_state property of a Model.
`MODEL_TYPE_IMAGE_CLASSIFICATION`	A constant which can be used with the model_type property of a Model.
`MODEL_TYPE_OBJECT_DETECTION`	A constant which can be used with the model_type property of a Model.
`average_precision`	Gets the average_precision of this Model.
`compartment_id`	[Required] Gets the compartment_id of this Model.
`confidence_threshold`	Gets the confidence_threshold of this Model.
`defined_tags`	Gets the defined_tags of this Model.
`description`	Gets the description of this Model.
`display_name`	Gets the display_name of this Model.
`freeform_tags`	Gets the freeform_tags of this Model.
`id`	[Required] Gets the id of this Model.
`is_quick_mode`	Gets the is_quick_mode of this Model.
`lifecycle_details`	Gets the lifecycle_details of this Model.
`lifecycle_state`	[Required] Gets the lifecycle_state of this Model.
`max_training_duration_in_hours`	Gets the max_training_duration_in_hours of this Model.
`metrics`	Gets the metrics of this Model.
`model_type`	[Required] Gets the model_type of this Model.
`model_version`	[Required] Gets the model_version of this Model.
`precision`	Gets the precision of this Model.
`project_id`	[Required] Gets the project_id of this Model.
`recall`	Gets the recall of this Model.
`system_tags`	Gets the system_tags of this Model.
`test_image_count`	Gets the test_image_count of this Model.
`testing_dataset`	Gets the testing_dataset of this Model.
`time_created`	[Required] Gets the time_created of this Model.
`time_updated`	Gets the time_updated of this Model.
`total_image_count`	Gets the total_image_count of this Model.
`trained_duration_in_hours`	Gets the trained_duration_in_hours of this Model.
`training_dataset`	[Required] Gets the training_dataset of this Model.
`validation_dataset`	Gets the validation_dataset of this Model.

Methods

__init__(**kwargs) Initializes a new Model object with values from keyword arguments.

LIFECYCLE_STATE_ACTIVE = 'ACTIVE'¶: A constant which can be used with the lifecycle_state property of a Model. This constant has a value of “ACTIVE”

LIFECYCLE_STATE_CREATING = 'CREATING'¶: A constant which can be used with the lifecycle_state property of a Model. This constant has a value of “CREATING”

LIFECYCLE_STATE_DELETED = 'DELETED'¶: A constant which can be used with the lifecycle_state property of a Model. This constant has a value of “DELETED”

LIFECYCLE_STATE_DELETING = 'DELETING'¶: A constant which can be used with the lifecycle_state property of a Model. This constant has a value of “DELETING”

LIFECYCLE_STATE_FAILED = 'FAILED'¶: A constant which can be used with the lifecycle_state property of a Model. This constant has a value of “FAILED”

LIFECYCLE_STATE_UPDATING = 'UPDATING'¶: A constant which can be used with the lifecycle_state property of a Model. This constant has a value of “UPDATING”

MODEL_TYPE_IMAGE_CLASSIFICATION = 'IMAGE_CLASSIFICATION'¶: A constant which can be used with the model_type property of a Model. This constant has a value of “IMAGE_CLASSIFICATION”

MODEL_TYPE_OBJECT_DETECTION = 'OBJECT_DETECTION'¶: A constant which can be used with the model_type property of a Model. This constant has a value of “OBJECT_DETECTION”

__init__(**kwargs)¶

Initializes a new Model object with values from keyword arguments. The following keyword arguments are supported (corresponding to the getters/setters of this class):

Parameters:

id (str) – The value to assign to the id property of this Model.
display_name (str) – The value to assign to the display_name property of this Model.
description (str) – The value to assign to the description property of this Model.
compartment_id (str) – The value to assign to the compartment_id property of this Model.
model_type (str) – The value to assign to the model_type property of this Model. Allowed values for this property are: “IMAGE_CLASSIFICATION”, “OBJECT_DETECTION”, ‘UNKNOWN_ENUM_VALUE’. Any unrecognized values returned by a service will be mapped to ‘UNKNOWN_ENUM_VALUE’.
is_quick_mode (bool) – The value to assign to the is_quick_mode property of this Model.
max_training_duration_in_hours (float) – The value to assign to the max_training_duration_in_hours property of this Model.
trained_duration_in_hours (float) – The value to assign to the trained_duration_in_hours property of this Model.
training_dataset (oci.ai_vision.models.Dataset) – The value to assign to the training_dataset property of this Model.
testing_dataset (oci.ai_vision.models.Dataset) – The value to assign to the testing_dataset property of this Model.
validation_dataset (oci.ai_vision.models.Dataset) – The value to assign to the validation_dataset property of this Model.
model_version (str) – The value to assign to the model_version property of this Model.
project_id (str) – The value to assign to the project_id property of this Model.
time_created (datetime) – The value to assign to the time_created property of this Model.
time_updated (datetime) – The value to assign to the time_updated property of this Model.
lifecycle_state (str) – The value to assign to the lifecycle_state property of this Model. Allowed values for this property are: “CREATING”, “UPDATING”, “ACTIVE”, “DELETING”, “DELETED”, “FAILED”, ‘UNKNOWN_ENUM_VALUE’. Any unrecognized values returned by a service will be mapped to ‘UNKNOWN_ENUM_VALUE’.
lifecycle_details (str) – The value to assign to the lifecycle_details property of this Model.
precision (float) – The value to assign to the precision property of this Model.
recall (float) – The value to assign to the recall property of this Model.
average_precision (float) – The value to assign to the average_precision property of this Model.
confidence_threshold (float) – The value to assign to the confidence_threshold property of this Model.
total_image_count (int) – The value to assign to the total_image_count property of this Model.
test_image_count (int) – The value to assign to the test_image_count property of this Model.
metrics (str) – The value to assign to the metrics property of this Model.
freeform_tags (dict(str, str)) – The value to assign to the freeform_tags property of this Model.
defined_tags (dict(str, dict(str, object))) – The value to assign to the defined_tags property of this Model.
system_tags (dict(str, dict(str, object))) – The value to assign to the system_tags property of this Model.

average_precision¶

Gets the average_precision of this Model. The mean average precision of the trained model.

Returns:	The average_precision of this Model.
Return type:	float

compartment_id¶

[Required] Gets the compartment_id of this Model. The compartment identifier.

Returns:	The compartment_id of this Model.
Return type:	str

confidence_threshold¶

Gets the confidence_threshold of this Model. The intersection over the union threshold used for calculating precision and recall.

Returns:	The confidence_threshold of this Model.
Return type:	float

defined_tags¶

Gets the defined_tags of this Model. Defined tags for this resource. Each key is predefined and scoped to a namespace. For example: {“foo-namespace”: {“bar-key”: “value”}}

Returns:	The defined_tags of this Model.
Return type:	dict(str, dict(str, object))

description¶

Gets the description of this Model. An optional description of the model.

Returns:	The description of this Model.
Return type:	str

display_name¶

Gets the display_name of this Model. A human-friendly name for the model, which can be changed.

Returns:	The display_name of this Model.
Return type:	str

freeform_tags¶

Gets the freeform_tags of this Model. A simple key-value pair that is applied without any predefined name, type, or scope. It exists for cross-compatibility only. For example: {“bar-key”: “value”}

Returns:	The freeform_tags of this Model.
Return type:	dict(str, str)

id¶

[Required] Gets the id of this Model. A unique identifier that is immutable after creation.

Returns:	The id of this Model.
Return type:	str

is_quick_mode¶

Gets the is_quick_mode of this Model. Set to true when experimenting with a new model type or dataset, so model training is quick, with a predefined low number of passes through the training data.

Returns:	The is_quick_mode of this Model.
Return type:	bool

lifecycle_details¶

Gets the lifecycle_details of this Model. A message describing the current state in more detail, that can provide actionable information if training failed.

Returns:	The lifecycle_details of this Model.
Return type:	str

lifecycle_state¶

[Required] Gets the lifecycle_state of this Model. The current state of the model.

Allowed values for this property are: “CREATING”, “UPDATING”, “ACTIVE”, “DELETING”, “DELETED”, “FAILED”, ‘UNKNOWN_ENUM_VALUE’. Any unrecognized values returned by a service will be mapped to ‘UNKNOWN_ENUM_VALUE’.

Returns:	The lifecycle_state of this Model.
Return type:	str

max_training_duration_in_hours¶

Gets the max_training_duration_in_hours of this Model. The maximum model training duration in hours, expressed as a decimal fraction.

Returns:	The max_training_duration_in_hours of this Model.
Return type:	float

metrics¶

Gets the metrics of this Model. The complete set of per-label metrics for successfully trained models.

Returns:	The metrics of this Model.
Return type:	str

model_type¶

[Required] Gets the model_type of this Model. What type of Vision model this is.

Allowed values for this property are: “IMAGE_CLASSIFICATION”, “OBJECT_DETECTION”, ‘UNKNOWN_ENUM_VALUE’. Any unrecognized values returned by a service will be mapped to ‘UNKNOWN_ENUM_VALUE’.

Returns:	The model_type of this Model.
Return type:	str

model_version¶

[Required] Gets the model_version of this Model. The version of the model.

Returns:	The model_version of this Model.
Return type:	str

precision¶

Gets the precision of this Model. The precision of the trained model.

Returns:	The precision of this Model.
Return type:	float

project_id¶

[Required] Gets the project_id of this Model. The OCID of the project that contains the model.

Returns:	The project_id of this Model.
Return type:	str

recall¶

Gets the recall of this Model. Recall of the trained model.

Returns:	The recall of this Model.
Return type:	float

system_tags¶

Gets the system_tags of this Model. Usage of system tag keys. These predefined keys are scoped to namespaces. For example: {“orcl-cloud”: {“free-tier-retained”: “true”}}

Returns:	The system_tags of this Model.
Return type:	dict(str, dict(str, object))

test_image_count¶

Gets the test_image_count of this Model. The number of images set aside for evaluating model performance metrics after training.

Returns:	The test_image_count of this Model.
Return type:	int

testing_dataset¶

Gets the testing_dataset of this Model.

Returns:	The testing_dataset of this Model.
Return type:	oci.ai_vision.models.Dataset

time_created¶

[Required] Gets the time_created of this Model. When the model was created, as an RFC3339 datetime string.

Returns:	The time_created of this Model.
Return type:	datetime

time_updated¶

Gets the time_updated of this Model. When the model was updated, as an RFC3339 datetime string.

Returns:	The time_updated of this Model.
Return type:	datetime

total_image_count¶

Gets the total_image_count of this Model. The number of images in the dataset used to train, validate, and test the model.

Returns:	The total_image_count of this Model.
Return type:	int

trained_duration_in_hours¶

Gets the trained_duration_in_hours of this Model. The total hours actually used for model training.

Returns:	The trained_duration_in_hours of this Model.
Return type:	float

training_dataset¶

[Required] Gets the training_dataset of this Model.

Returns:	The training_dataset of this Model.
Return type:	oci.ai_vision.models.Dataset

validation_dataset¶

Gets the validation_dataset of this Model.

Returns:	The validation_dataset of this Model.
Return type:	oci.ai_vision.models.Dataset