Create new dataset

Create a new dataset in a client.

** From 1st January 2020, one needs to call Process Upload API after this API call to complete preprocessing.
URL
POST https://tools.deepen.ai/api/v2/clients/{clientId}/datasets​
Request
Path parameters
Parameter name
Parameter type
Description
clientId
string
Client Id obtained from Deepen AI
Request body
Property name
Property type
Description
files
array
Array of metadata objects, each representing a file to be uploaded. Please see the example object below for the structure of the metadata object. For datasets of dataset_type ‘images’’, the metadata should be of a zip file of all images to be uploaded as part of the dataset. For datasets of dataset_type ‘video’, the metadata should be of an mp4 of the video to be uploaded as part of the dataset.
dataset_format
string
The format in which the dataset is uploaded for ‘3d’ dataset types. Can take one of the following values :
1.json
2.default
Not required for dataset_type other than ‘3d’
dataset_type
string
The type of uploaded dataset:
3d 
video
images 
dataset_name
string
Name of the uploaded dataset
labelling_mode
string
Labelling format in the dataset:
label_by_label (For sequence datasets)
frame_by_frame (For single frame datasets - default)
labelling_profile_id
string
Labelling profile id
This is the profile id of the profile from which to get the labelling instructions.
labelling_profile
object
LabellingProfileResource indicating the labelling instructions. Either labelling_profile or labelling_profile_id is necessary to include labelling instructions with the dataset.
tags
array
Array of TagResource
user_scopes
array
Array of DatasetUserScopeResource
user_group_scopes
array
Array of DatasetUserGroupScopeResource
Example body
{
       'dataset_name': 'testDataset',
       'dataset_type': '3d',
       'fps': 10,
       'labelling_profile': {'pipeline_spec': [{'stage_id': 'Labelling', 'can_edit': True, 'skills': {'box': {}, 'point': {}, 'polygon': {}, 'lane': {}, '3d_bbox': {}, '3d_point': {}, '3d_instance_point': {}, '3d_polygon': {}, '3d_polyline': {}}}, {'stage_id': 'QA', 'can_edit': False, 'skills': {'box': {}, 'point': {}, 'polygon': {}, 'lane': {}, '3d_bbox': {}, '3d_point': {}, '3d_instance_point': {}, '3d_polygon': {}, '3d_polyline': {}}}], 'features': {'box': {'attributes': {}, 'label_category_ids': []}, 'lane': {'attributes': {}, 'label_category_ids': []}, 'polygon': {'attributes': {}, 'label_category_ids': []}, 'point': {'attributes': {}, 'label_category_ids': []}, '3d_bbox': {'attributes': {}, 'label_category_ids': []}, '3d_polyline': {'attributes': {}, 'label_category_ids': []}, '3d_polygon': {'attributes': {}, 'label_category_ids': []}, '3d_point': {'attributes': {}, 'label_category_ids': []}, '3d_instance_point': {'attributes': {}, 'label_category_ids': []}}, 'instructions': {'text': ''}, 'notification_url': ''}, 
       'labelling_mode': 'frame_by_frame',
       'dataset_format': 'default',
       'sensor_maker': None,
       'files': [{'file_size': 16513471, 'file_type': 'application/zip'}]
}
​
Response
Returns an array of resumable upload urls on successful completion

Response body
Property name
Property type
Description
files
array
Array of metadata objects, each representing a file to be uploaded. Please see the example object below for the structure of the metadata object. Each metadata object has a Google cloud storage resumable upload url, to which the file has to be uploaded. Please see google cloud storage documentation at https://cloud.google.com/storage/docs/json_api/v2/how-tos/resumable-upload to learn how to upload the file using the url.
dataset_id
string
The new dataset id created for the uploaded dataset
Example
{


    'dataset_id': 'BBZztvi0Z9TC',
'files': [{'resumable_upload_url': 'https://www.googleapis.com/upload/storage/v2/b/deepenai-dev-rannotateclientdata/o?uploadType=resumable&name=rannotate_client_uploaded_data/8cz4s0r1/defaultproject/BBZztvi0Z9TC/3d_data.zip&upload_id=AAANsUnQh_s03FsS-iGuvfD9n3ABpmvLxV8-Yi86g-QwGrtntj3HfYE8e_l1iDbeKAp06MXNGqvbotpgti1n3yjQEF0', 'signed_form_data': None, 'file_size': 16513471, 'file_type': 'application/zip'}]
}
Please use the below command or follow this link to upload the data
curl -v -X PUT -H 'Expect:' --upload-file '<path to zip file>' '<resumable upload url>'
Once the dataset zip file is uploaded, you need to call the process uploaded data api to process the zip file and make it ready for labelling. 

Last modified 9mo ago

Parameter name	Parameter type	Description
clientId	string	Client Id obtained from Deepen AI

Property name	Property type	Description
files	array	Array of metadata objects, each representing a file to be uploaded. Please see the example object below for the structure of the metadata object. For datasets of dataset_type ‘images’’, the metadata should be of a zip file of all images to be uploaded as part of the dataset. For datasets of dataset_type ‘video’, the metadata should be of an mp4 of the video to be uploaded as part of the dataset.
dataset_format	string	The format in which the dataset is uploaded for ‘3d’ dataset types. Can take one of the following values : 1. json 2. default Not required for dataset_type other than ‘3d’
dataset_type	string	The type of uploaded dataset: 3d video images
dataset_name	string	Name of the uploaded dataset
labelling_mode	string	Labelling format in the dataset: label_by_label (For sequence datasets) frame_by_frame (For single frame datasets - default)
labelling_profile_id	string	Labelling profile id This is the profile id of the profile from which to get the labelling instructions.
labelling_profile	object	LabellingProfileResource indicating the labelling instructions. Either labelling_profile or labelling_profile_id is necessary to include labelling instructions with the dataset.
tags	array	Array of TagResource
user_scopes	array	Array of DatasetUserScopeResource
user_group_scopes	array	Array of DatasetUserGroupScopeResource