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Introduction

Dataturks API allows you to seamlessly integrate the labeled dataset in your ML training or evaluation flow.

For each iteration of your model improvement, you can push new data to be annotated by your labeling team and then pull the annotated data in your retraining flow.

You can also use Dataturks to continuously track your model performance by uploading your model outputs and have your labeling team validate it and generate week-on-week accuracy numbers.

Overview

Getting ‘Org Name’ and ‘Project Name’:\nUpload/Download APIs take as path params, the organization name and the project name.\n‘Org Name’ and ‘Project Name’ are as shown on your Dataturks Project Page on the website.

Authentication

All APIs take a ‘key’ and ‘secret’ param in the header. These key-secret\npairs are associated with a user and allows the same permission to the user as she has on the\nDataturks website, ex: if she is an admin of a project, she can upload data to the project etc. Please mail us to get your key/secret pair.

Error Codes

Specific to each API.

Rate limit

Specific to each API

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Possible values for TaskType are [TEXT_CLASSIFICATION, POS_TAGGING,\nPOS_TAGGING_GENERIC, TEXT_MODERATION, DOCUMENT_ANNOTATION, IMAGE_CLASSIFICATION,\nIMAGE_POLYGON_BOUNDING_BOX_V2, VIDEO_CLASSIFICATION, VIDEO_BOUNDING_BOX]

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Update project rules.

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Will upload data items to your project. You can send the data as a file as POST form data with\nthe field name ‘file’ . The file uploaded depends upon the project type, for example for POS\nprojects you can upload a single text file or for a document annotation you can upload a single\nfile or a zip file etc.

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You can also upload a partially tagged/pre-tagged data using the APIs. You upload a file where\neach lines is a JSON describing one data item (the item and its annotations).

(A good way to validate this would be to download results from an existing project and use that file and\nupload in the above API.)

The JSON is the Dataturks annotation format, the same format as you get when you download\ndata from Dataturks.

Also since the upload contains both the text and the annotations, all the items created would be\nin the 'preTagged' state. An annotator can go through each of these via \"Start Tagging\" and then keep editing one by one.

Also, in the \"PreTagged\" state, an annotator would be able to see the pre-tagged markings and can even evaluate the markings as \"Correct/Incorrect\".

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