Annotation request is the core concept in the organization of annotation work at Kognic. The request's configuration specifies what data to annotate (Input batch), how to annotate the data (Annotation Instruction: Taxonomy and guideline), which process the data should be produced by (Workflow), and who should annotate and quality-assure the data (Team).

You can create requests in multiple ways:

This chapter explains how to create a request in an existing project. If you want to create a new project and add one or multiple requests to it, we recommend you start by reading the chapter Guide: Create a new project.

When creating a request from scratch, you can freely specify what input type and workflow the request should use.

If a request in the project uses the same input type and workflow as you want for your new request, you can also create a new request using the existing one as a template.

To get started, open the project in which you want to create a new request. Then locate the "Create request" button at the top right corner of the project page.

Name the request When naming the request, ideally, use a straightforward name that refers to the type of annotation you plan to use it to produce. Try to avoid using names made up of random letters and numbers.

Input batch external ID Optional external ID that can be used to target the project when using external APIs.

Name the input batch When creating a request, you need to create a new input batch alongside it. The input batch is referenced when uploading your data to the request.

An input batch is a group of inputs. An input is a set of sensor data you want to annotate. It usually consists of at least one image/frame. It can also contain images from several cameras, a point cloud, a video, or a sequence of images. Read more in our API Documentation. 

Select an annotation type Kognic uses annotation types to categorize the annotations produced in different requests. Select the one that best matches the type of annotations you plan to produce in your request.

The organization with the request role Producer is responsible for producing annotated data in the request. Users from this organization are allowed more detailed monitoring and management options and can configure the request team in detail. All to ensure they can successfully monitor and manage the production process.

The input type decides what data type you can upload to your newly created input batch and later annotate in the request.

The available input types are:

In this step you can select a revision of a annotation instruction you have created with our tools.

An Annotation Instruction is a specification of what you want to annotate and a guidance of how you want it to be annotated.

A revision is a version of your instruction that has been used in production. As you learn more about your dataset, you probably want to update your instruction, which is handled by creating a new revision.

The request workflow determines the steps used to produce annotations and in what order. They define what type of steps (tasks) to complete before we have produced a deliverable annotation. Below we will describe the available workflows.

Annotate + Review

Every input is first annotated and then reviewed. If the annotation's quality is insufficient, the reviewer can reject the annotation. If rejected, the annotation is sent for a review correction and then reviewed again. This loop continues until the annotation is accepted, at which point the annotated input becomes delivery-ready.

Annotate + Correct + Review

Every input is first annotated, then corrected, and lastly, reviewed. If the annotation's quality is insufficient, the reviewer can reject the annotation. If rejected, the annotation is sent for a review correction and then reviewed again. This loop continues until the annotation is accepted, at which point the annotated input becomes delivery-ready.

Experimental workflows

Our flexible workflows consist of phases, which can be added, removed or displayed in any order to suit your unique needs. We currerntly have two flexible workflows available for use, with more planned for the future.

You can learn more about our flexible workflows in the chapter Flexible Workflows.

The error types are available in the Feedback Tools during Review tasks, and during follow-up Correction tasks. If your organization has many error types configured, you might want to select a subset of error types that are relevant for this request. You can learn more about error types on the page Error Types.

Once everything above has been specified, you can create your new request. 🎉

After creating your request, you need to ensure the following things are done:

When using an existing request as a template, the new request will use the same input type and workflow as the original request. You also have the option of using the same annotation instruction, which saves you time in preparing the request for production.

If you don't want your new request to use the same input type and workflow as an existing request in the project, create the request from scratch instead.

To get started, open the request you want to use as a template for your new request. Then open the context menu at the top right corner of the page, and select the menu option "Use as template".



Name the request When naming the request, ideally, use a straightforward name that refers to the type of annotation you plan to use it to produce. Try to avoid using names made up of random letters and numbers.

Name the input batch When creating a request, you need to create a new input batch alongside it. To this input batch, you later upload your data to have it annotated in the request.

An input batch is a group of inputs. An input is a set of input data you want to annotate. It usually consists of at least one image/frame. It can also contain images from several cameras, a point cloud, a video, or a sequence of images.

Select an annotation type (only applicable if you don't use the same annotation instruction) Kognic uses annotation types to categorize the annotations produced in different requests. Select the one that best matches the type annotations you plan to produce in your request.

Once everything above has been specified, you can create your new request. 🎉

After creating your request, you need to collaborate with Kognic to ensure the request is ready for production. This means ensuring the following things are done: