Dataset

dataset_client.create_dataset(body)

Create a new dataset with the specified name, description, and other details.

Table:Input parameters summary:

Field	Input	Type	Description
dataset_name	body	str	The name of the new dataset to create
dataset_description	body	str	A description for the new dataset
dataset_type	body	str	The type of the new dataset (e.g. Image, Text, Audio, etc.).
item_format	body	str	The format of the dataset items (e.g. image/jpeg, text/plain, audio/mpeg, etc.)
metadata	body	dict	A dictionary of metadata to associate with the new dataset.
s3IntermediateUrl	body	str	The S3 URL where the dataset items are processed
aws_credentials_enabled	body	bool	Whether AWS credentials are enabled for the dataset
aws_credentials	body	dict	A dictionary containing AWS credentials for the dataset

Sample Request Body

from pprint import pprint
from tensoract.client import Tensoract


# Initialize Tensoract client
dataset_client = Tensoract(api_url="YOUR_API_URL",api_key="YOUR_API_KEY")

    body={
    "dataset_name": "Test-Dataset-API",
    "dataset_description": "This is a test Dataset",
    "dataset_type": "Image",
    "item_format": "image/tiff",
    "metadata": {
        "Dataset": "Image Dataset"
    },
    "s3IntermediateUrl": "s3://************************************",
    "aws_credentials_enabled": true,
    "aws_credentials": {
        "awsKey": "***********",
        "awsSecret": "**************",
        "awsRegion": "***********",
        "awsType": "key"
    }
    }
    pprint(dataset_client.create_dataset(body))

Table:Response summary:

Field	Type	Instructions
dataset_id	str	Id of the dataset.
value	str	Description or message indicating the result.
status	str	The status of the operation

Sample Response

{
    "dataset_id": "e20859abab70f7df3fb0b7c7",
    "value": "Dataset updated",
    "status": "success"
}

dataset_client.delete_dataset(dataset_id)

Delete Dataset.

Table:Input parameters summary:

Field	Input	Type	Description
dataset_id	body	str	The Id of the dataset to delete

from pprint import pprint
from tensoract.client import Tensoract


# Initialize Tensoract client
dataset_client = Tensoract(api_url="YOUR_API_URL",api_key="YOUR_API_KEY")

# Invoke delete_dataset method
response = dataset_client.delete_dataset(dataset_id="8bc05ec26ab161e218a0e842")
pprint(response)

Table:Response summary:

Field	Type	Description
status	str	The status of the operation
value	str	The result or value of the operation

Sample Response

{
     "status": "success",
     "value": "dataset deleted"
}

dataset_client.get_dataset(dataset_id)

Get a dataset by ID.

Table:Input parameters summary:

Field	Input	Type	Description
dataset_id	body	str	The Id of the dataset to retrieve

from pprint import pprint
from tensoract.client import Tensoract


# Initialize Tensoract client
dataset_client = Tensoract(api_url="YOUR_API_URL",api_key="YOUR_API_KEY")

# Invoke get_project method
response = dataset_client.get_dataset(dataset_id="9373f3f9d3f1400cfba6ac6a")
pprint(response)

Table:Response summary:

Field	Type	Description
dataset_id	str	The Id of the dataset
dataset_name	str	The name of the new dataset to create
dataset_description	str	A description for the dataset
dataset_type	str	The type of the dataset
dataset_versions	list	A list of dictionaries containing version information for the dataset.
item_format	str	The format of the dataset items
metadata	dict	A dictionary containing metadata for the dataset.
aws_credentials_enabled	bool	Whether AWS credentials are enabled for the dataset
aws_credentials	dict	A dictionary containing AWS credentials for the dataset
s3IntermediateUrl	str	The S3 URL for intermediate data

Sample Response

{
    "dataset_id": "9373f3f9d3f1400cfba6ac6a",
    "dataset_name": "Test-Dataset-Recipes",
    "dataset_type": "PDFOCR",
    "dataset_versions": [
        {
        "id": 0,
        "items": 29,
        "name": "V.1",
        "locked": false,
        "created": 1690173205,
        "modified": 1690173205
        }
    ],
    "dataset_items": 29,
    "metadata": {
        "Dataset": "Recipes"
    },
    "company": "60f38299446de8dabe9207e5",
    "company_name": "Objectways",
    "aws_credentials_enabled": true,
    "aws_credentials": {
        "awsType": "key",
        "awsKey": "********************",
        "awsSecret": "****************************************",
        "awsRegion": "*********"
    },
    "s3IntermediateUrl": "*******************************"
}

dataset_client.list_datasets(dataset_id, dataset_name, active)

List datasets.

Table:Input parameters summary:

Field	Input	Type	Description
dataset_id	body	str	The Id of the dataset
dataset_name	body	str	The name of the dataset
active	body	bool	Whether to filter datasets by active status

Sample Request Body

{
    from pprint import pprint
    from tensoract.client import Tensoract


    # Initialize Tensoract client
    dataset_client = Tensoract(api_url="YOUR_API_URL",api_key="YOUR_API_KEY")

    # Invoke list_datasets method
    response = dataset_client.list_datasets(dataset_id=None,dataset_name=None,active=True)
    pprint(response)
}

Table:Response summary:

Field	Type	Description
dataset_id	str	The Id of the dataset
dataset_name	str	The name of the dataset
dataset_description	str	A description for the dataset
dataset_type	str	The type of the dataset
dataset_versions	list	A list of dictionaries containing version information for the dataset.
company	str	The Id of the company associated with the item.
company_name	str	The name of the company associated with the item.

Sample Response

[
        {
        "dataset_id": "c8a04fbf7c8f95ef8912338f",
        "dataset_name": "Test Dataset",
        "dataset_type": "Image",
        "dataset_versions": [
        {
            "id": 0,
            "items": 1,
            "name": "Base version",
            "locked": true,
            "created": 1657526913,
            "modified": 1657526913
        },
        {
            "id": 1,
            "items": 59,
            "name": "Version 2",
            "locked": true,
            "created": 1657527052,
            "modified": 1657527052
        }
        ],
        "company": "60f38299446de8dabe9207e5",
        "company_name": "Objectways"
    },
    {
        "dataset_id": "bd35da16cd39283f119454cc",
        "dataset_name": "Test Dataset 3",
        "dataset_type": "Image",
        "dataset_versions": [
        {
            "id": 0,
            "items": 1,
            "name": "V.1",
            "locked": true,
            "created": 1657708086,
            "modified": 1657708086
        },
        {
            "id": 1,
            "items": 5,
            "name": "V.2",
            "locked": true,
            "created": 1657709319,
            "modified": 1657709319
        },

        ],
        "company": "60f38299446de8dabe9207e5",
        "company_name": "Objectways"
    }
]

dataset_client.update_dataset(dataset_id, body)

Update Dataset.

Table:Input parameters summary:

Field	Input	Type	Description
dataset_id	body	str	The Id of the dataset
dataset_name	body	str	The name of the new dataset to create
dataset_description	body	str	A description for the dataset
dataset_type	body	str	The type of the dataset
dataset_versions	body	list	A list of dictionaries containing version information for the dataset.
item_format	body	str	The format of the dataset items
metadata	body	dict	A dictionary containing metadata for the dataset.
aws_credentials_enabled	body	bool	Whether AWS credentials are enabled for the dataset
aws_credentials	body	dict	A dictionary containing AWS credentials for the dataset
s3IntermediateUrl	body	str	The S3 URL for intermediate data

Sample Request Body

from pprint import pprint
from tensoract.client import Tensoract


# Initialize Tensoract client
dataset_client = Tensoract(api_url="YOUR_API_URL",api_key="YOUR_API_KEY")

body={
        "dataset_name": "Test-Dataset-API",
        "dataset_description": "Update dataset",
        "dataset_type": "Image",
        "item_format": "image/tiff",
        "metadata": {
            "Dataset": "Image Dataset"
        },
        "s3IntermediateUrl": "s3://************************************",
        "aws_credentials_enabled": true,
        "aws_credentials": {
            "awsKey": "***********",
            "awsSecret": "**************",
            "awsRegion": "***********",
            "awsType": "key"
        }
    }
response = dataset_client.update_dataset(dataset_id="85bfac4fb66d935312a373ec",body=body)
pprint(response)

Table:Response summary:

Field	Type	Description
dataset_id	str	The ID of the dataset
dataset_name	str	The name of the new dataset to create
dataset_description	str	A description for the dataset
dataset_type	str	The type of the dataset
dataset_versions	list	A list of dictionaries containing version information for the dataset.
item_format	str	The format of the dataset items
metadata	dict	A dictionary containing metadata for the dataset.
aws_credentials_enabled	bool	Whether AWS credentials are enabled for the dataset
aws_credentials	dict	A dictionary containing AWS credentials for the dataset
s3IntermediateUrl	str	The S3 URL for intermediate data

Sample Response

{
    "dataset_id": "85bfac4fb66d935312a373ec",
    "dataset_name": "Test-Dataset-API",
    "dataset_type": "Image",
    "dataset_description": "Update Dataset",
    "dataset_versions": [
        {
        "id": 0,
        "items": 0,
        "name": "V.1",
        "locked": false,
        "created": 1678442477,
        "modified": 1678442477
        }
    ],
    "item_format": "image/tiff",
    "metadata": {
        "Dataset": "Image Dataset"
    },
    "company": "60f38299446de8dabe9207e5",
    "aws_credentials_enabled": true,
    "aws_credentials": {
        "awsKey": "********************",
        "awsSecret": "****************************************",
        "awsRegion": "*********",
        "awsType": "key"
    },
    "s3IntermediateUrl": "s3://************************************",

}