Object recognition & detection

In this tutorial, you will learn how to run object recognition in Toloka. We will use a project preset designed specifically for this type of data labeling.

Object recognition is a type of data labeling task with an image and an editor for selecting an image area.

Tolokers look at the image and select the objects that you need to detect. After you collect all the labeled images, you can apply your dataset for computer vision training.

Prerequisites

Before you begin:

Make sure you are registered in Toloka as a requester.
Top up your Toloka account. If you are unsure about the budget, you can do that later in this tutorial. Toloka will display the budget estimate for your project.

Create a project

We recommend starting with a project preset for easier configuration and better results.

Follow this link, or create a project manually:
1. Click Create a project.
2. Click Do it myself.
3. Select the Object recognition & detection preset.
Click Choose this preset in the pop-up tab.
In the General information section, add the project name and description:
- Name to show Tolokers: In 2–5 words, state the general idea of the project.
- Description for Tolokers: In a couple of sentences, explain what you expect Tolokers to do. This is just an overview. You will write instructions later.
In the Task interface section, set up what your tasks will look like. This preset has a task template with validation, keyboard shortcuts, and task layout pre-configured.

Note
This tutorial uses Template Builder, but you can use the HTML/JS/CSS editor for the same purpose.
1. Using the Visual editor, set up your task in the Config section:
  - Paste link to a sample image: This image is only used to display the task interface preview on the right.
  - Choose the shape for outlining objects in photos: All tasks in a project use the same shape.
2. Select the I want to outline multiple types of objects checkbox if you need to detect more than one category of objects in an image. Replace the samples with your types:
  - Object name for Tolokers: This is the label that Tolokers will see. Make sure it is clear and correct.
  - Name in labeling results: This is the value you will see in the file with the labeling results.
3. Raw task data is stored in the XSLX, TSV, or JSON format. The labeling results are presented in a TSV file. The Data specification section determines which parameters these files might contain.
  
  Click Show specifications and check the values:
  - Input data: Parameters in the file with raw task data.
  - Output data: Parameters in the file with labeling results.
  Input data and Output data match the task interface you set up in Template Builder. Check that there are fields for all data types you use for your tasks, and for the ones you want to see in the results file.
In the Instructions for Tolokers editor, enter the instructions Tolokers will see when they start doing your tasks. You can add text, tables, and images to your instructions.

In this type of project, Tolokers will select objects in images with the shape you’ve specified in the Config section.

Check the sample text of the instructions, and update it to fit your project.

Tip
When writing instructions, remember that most Tolokers don’t know anything about your tasks beforehand. Make sure your instructions are as clear as possible, but not too wordy. For successful data labeling, try to strike a balance between covering all the essentials and keeping it short. Learn more in our knowledge base.
In the upper-right corner, click Save.

Learn more about working with the project in the Project section.

Create a pool

A pool is a set of tasks sent out to Tolokers at the same time. One project can have many pools. When creating a pool, you set up pricing, audience filters for Tolokers, and quality control.

Click Create new pool on the project page.
Select the value in the Pool type drop-down list.

Pool types

Note
If the price per task suite is zero, you must select the pool type.
Set the Pool name (visible only to you) field. Only you will see this pool name on the project page.
Specify the pool description which will be displayed instead of the project description in the task list for Tolokers. By default, Tolokers see the description from the project settings. To use a different description, uncheck the Use project description box and set Public description. If necessary, click + Private comment to add a private project description that only you will see.
Click Create.
At the Select the audience for your task step, set up filters to select Tolokers for your pool.
1. Clear My tasks may contain shocking or pornographic content if your project has none of those.
2. To select Tolokers based on their language, location, age, gender, and other parameters, click the Add filter button.
  
  For example, add the Languages filter:
3. Tasks in pools will automatically be available in the web version of Toloka and the mobile app. If you want to change the default settings and limit the visibility of the task for any of the versions, add the Client filter and select the desired value: Toloka web version or Toloka for mobile.
4. Use the Speed/quality balance slider to change the number of Tolokers who can see your tasks. Move the slider to the right to exclude Tolokers with lower ratings from participating in your project.
At the Setup quality control step, set quality control rules for more accurate results:
1. Click the Review task responses manually toggle, and specify the number of days for checking the task in the Review period in days field.
  
  What is manual review?
2. Keep the pre-configured Fast responses rule as is. This rule filters out Tolokers who complete tasks too fast. The default settings mean that Tolokers are banned from the project for 1 day if they complete tasks in 4 out of 5 task suites in less than 15 seconds.
3. Delete the pre-configured Majority vote rule.
4. Click Add a quality control rule → Results of manual review, and enter the following values:
  
  This means that if 35% or more of a Toloker's responses are rejected, the Toloker is banned and can't access your tasks for 15 days. The rule takes effect after 3 responses of the Toloker are reviewed.
At the Add optional pool settings step, specify the Time per task suite, sec.

It should be long enough to read the instructions and wait for task data to download (for example, 1,200 seconds).
At the Set the task price and overlap step, set up how much a single task will cost for you.
1. In Price per task suite, set the amount of money to pay per task suite done by one Toloker. A task suite is a page with a number of tasks. It can contain one or several tasks.
  
  If the tasks are simple, you can add 8–10 tasks per suite.
2. In the Overlap field, define how many Tolokers must do each task.
  
  For image area selection tasks, it is usually 1. This means that each task will have 1 response.
At the Prepare and upload data step, upload your task data.
1. Attach a prepared dataset or media files.
  1. To download a template, click one of the buttons:
    - Template in XLSX
    - Template in TSV
    - Template in JSON
    For this type of project, the file with tasks must have one parameter. Its name equals INPUT:image, and the values are links to the images.
    INPUT:image https://tlk.s3.yandex.net/sdc/photos/0c7b15d0f4e5db0416189afe6486f3cb.jpg https://tlk.s3.yandex.net/sdc/photos/3e5d32e31dfd50fe826fd46b761481cf.jpg https://tlk.s3.yandex.net/sdc/photos/0fb80721932aa59ecc684141433170b6.jpg
  2. Open the downloaded file, and replace the sample links with links to your images.
  3. Click Select prepared dataset, and upload the file you’ve just made.
2. Click Continue.
3. Tasks are shown to Tolokers in suites. A suite is a single page with multiple tasks. Define how many tasks to include per suite:
  - General tasks: These are tasks for Tolokers to label.
  - Control tasks: These are tasks with predefined answers used to control the quality of responses. You don’t need control tasks in area selection projects.
  - Training tasks: These are tasks with predefined answers and explanations for Tolokers. Normally you use training tasks in separate training pools. You don’t have to include them.
  For example, you can add 8 general tasks per suite:
4. Click Combine tasks into suites.
At the Double-check your project and try out tasks step, check how the task will look from the Toloker's point of view.

Note
This step will be enabled after you complete the previous steps. You can skip this step by clicking Do it later.

After all the steps, you'll see the Set up is finished and your pool is ready for labeling tip on the pool page.

Start labeling

Make sure you have topped up your account.
To send the tasks to Tolokers and begin the labeling process, click Start labeling.
In the pop-up panel, review the budget and click Launch.

See the results

Track the labeling progress on the pool page. You can start the review when the first results are received.

After the specified time period, all responses are automatically accepted, regardless of their quality.

Go to the pool, and click Review assignments.
Choose an assignment.
Check the responses, and click Accept or Decline. For rejected responses, enter a comment to specify the reason.

Note
To learn about other ways of review, see the Reviewing Tolokers' responses section.
After checking all the assignments, click Download results.

You will get the TSV file with the labeling results. The point coordinates in the file are presented in JSON.

Troubleshooting

Do I need to convert all the images in the task to the same size or can they be different?

How do I mark up triangles so that they close automatically when the third point is selected?

How do I create a task for selecting objects in images?

I have a task for area selection in an image. What should the Toloker do if there is no selectable object in the image?

How much would 2000 images with a large number of different types of selectable objects cost? How do I create a task for this amount of work?

How do I implement selection of 3 different areas in an image? Select the name, image, and price in the product page screenshot.

What are the input data in the case of object labeling in an image: the coordinates of the object relative to the image, or the coordinates of the object in the Toloka Toloker window?

How do I use control and training tasks in the standard template with an area selection editor?