Tutorials for popular tasks
Using tutorials, you'll learn how to post tasks in Toloka. Choose the tutorial that is most similar to your task.
Before you start
Make sure you're registered as a requester. We recommend that you go through tutorials in the sandbox.
List of examples
- Images
- Object classification is a multiple choice task. Examples are moderating content or grouping images by category.
- Side-by-side image comparison — The performer compares pairs of images, illustrations, or interfaces.
- Object recognition and area selection — The performer has to mark the areas on an image that contain the specified object. These tasks are easier to run in the web version.
- Object recognition and area selection (example with decomposition) — An example of dividing a task for selecting objects into three projects: filtering out inappropriate images, selecting objects, and reviewing assignments.
- Video
- Video classification is a multiple choice task. For example, moderation of content, evaluation of video for noise and defects, or video classification by specified categories.
- Audio
- Audio transcription — The performer receives an audio recording and has to type the text they hear. Checking such tasks can be assigned to other performers as a classification task.
- Voice recording — The performer receives a phrase or text fragment to record and has to attach the audio file as the response. These tasks are easier to run in the mobile app for Android and iOS.
- Texts
- Tone evaluation and content moderation — The performer checks the text for compliance with the rules.
- Data enrichment
- Survey — Set requirements for respondents and take a poll.
- Business information — A task in which performers search for data about businesses online.
- Business information (example with decomposition) — Type of task for searching and processing relevant data. For example, find similar shoes in an online store or determine which of the found objects is more similar to the original one.
- Field tasks
Field tasks are completed in the Toloka mobile app for Android and iOS.
- Collecting offline data — The performer has to come to a point on the map, check for something, and take photos.
- Price monitoring — The performer comes to the point and takes photos of the store's front, product, and its price tag.
- Product monitoring — The performer comes to the store, takes a photo of its front, finds the relevant section inside, and takes a photo of the rack with a certain brand of products.
- Data collection: Organizations — The performer comes to the point, takes a picture of the outside of the organization, and photographs the object inside from different angles.
- Street object control — The performer comes to the point, finds an object on the street, photographs it from different sides, and takes a picture of the address plate.
- Level 1. Tutorials using a single project are suitable for beginners. Go through at least one tutorial that is most similar to your task.
- Object classification is a multiple choice task. Examples are moderating content or grouping images by category.
- Side-by-side image comparison — The performer compares pairs of images, illustrations, or interfaces.
- Object recognition and area selection — The performer has to mark the areas on an image that contain the specified object. These tasks are easier to run in the web version.
- Audio transcription — The performer receives an audio recording and has to type the text they hear. Checking such tasks can be assigned to other performers as a classification task.
- Voice recording — The performer receives a phrase or text fragment to record and has to attach the audio file as the response. These tasks are easier to run in the mobile app for Android and iOS.
- Video classification is a multiple choice task. For example, moderation of content, evaluation of video for noise and defects, or video classification by specified categories.
- Tone evaluation and content moderation — The performer checks the text for compliance with the rules.
- Survey — Set requirements for respondents and take a poll.
- Business information — A task in which performers search for data about businesses online.
- Level 2. Field tutorials — If you need to post field tasks, go through a tutorial at this level. If not, you can skip it.
Field tasks are completed in the Toloka mobile app for Android and iOS.
- Collecting offline data — The performer has to come to a point on the map, check for something, and take photos.
- Price monitoring — The performer comes to the point and takes photos of the store's front, product, and its price tag.
- Product monitoring — The performer comes to the store, takes a photo of its front, finds the relevant section inside, and takes a photo of the rack with a certain brand of products.
- Data collection: Organizations — The performer comes to the point, takes a picture of the outside of the organization, and photographs the object inside from different angles.
- Street object control — The performer comes to the point, finds an object on the street, photographs it from different sides, and takes a picture of the address plate.
- Level 3. Tutorials using several projects — Learn how to decompose a task.
- Object recognition and area selection (example with decomposition) — An example of dividing a task for selecting objects into three projects: filtering out inappropriate images, selecting objects, and reviewing assignments.
- Business information (example with decomposition) — Type of task for searching and processing relevant data. For example, find similar shoes in an online store or determine which of the found objects is more similar to the original one.
If you didn't find a suitable example, use general instructions for launching and setting up projects.
You can contact us or our partners if you need help with your project overall or with individual steps like editing tasks.
Learn more about how to set up pricing and see examples of cost for different types of tasks.
Troubleshooting
- Sorting images containing an object.
- Create a task using the “Image classification” template.
- Sort the images containing the object you are looking for.
- Show the image to the performer and ask if the object is in the image. Response options: Yes/No.
- Selecting objects in images.
- Select the object in the images you obtained after the previous project. You already have such a project. Run the task with non-automatic acceptance.
- Use the quality control rules: fast responses, non-automatic acceptance, and post-review re-assessment. Description of rules with examples.
- Reviewing object selection assignments.
- Create a task using the object selection template.
- Hide the editor and ask whether the object is selected correctly. Response options: Yes/No.
- In the input data, pass the images and coordinates of the labeled objects from the previous task.
To prevent the users who worked on the second project from doing the review, assign a skill to them. Use this skill as a filter in the pools of the third project.
- Select an arbitrary area in the image (for example, put a square in the upper-right corner). In this case, the project instructions for reviewers should also reflect this.
- Ask the performer to skip the task and report it in a personal message. Messages are reviewed by the requester. If the object is truly missing, the task is deleted from the pool by resetting the overlap.
- Add an additional “No object” checkbox to the interface. Make sure that your JS checks that either the object is selected or the checkbox is enabled. In this case, add information about the checkbox value in the review task interface.
- In the project, the input field where you pass the file link has the “string” type.
- The component in the task template uses the "proxy" expression.
- The format of relative links in the TSV file with tasks is correct: <unique name>/<file path and name>.
- Use the “Side-by-side image comparison” template.
- In the TSV file, specify the links to the compared images.
- In the file, create the tasks where all the images will be compared in pairs:
Image 1 and Image 2
Image 1 and Image 3
- Image 2 and Image 3
- Process the results.
- Create a project from an empty template.
- Write your question in the HTML block.
- If you need an extensive response, add the required number of text entry components.
- If you need a short response, add the required number of string entry components.
- Come up with a name for each of the components and create a matching number of string-type output fields with the same names. They will be used to save responses.
- Make all the output fields mandatory.
- Make the input field auxiliary. It will only be used to create a TSV file with tasks.
- Come up with a name for the input field and set the string type for it (see the step-by-step guide on creating a survey).
You can create such an assignment based on the classification template. Show a product image and ask the question: "Does the product match the query?" Add two radio buttons for responses: “yes” and “no”.
onKey: function(key) {
var el = this.getDOMElement().querySelector(".image-annotation-editor__shape-polygon");
if (key === 'D') {
el.click();
el.classList.add('image-annotation-editor__shape_active')
}Use the C shortcut for closing areas.
You can also use the library to customize the keyboard shortcuts for your tasks.
In the case of crowdsourcing, it's better to break down this task. The simpler the task, the cheaper it is and the better the quality of the final result. The cost of labeling a single class of objects in photos might be about $0.01.
Use the “Object selection in an image” template as a basis. See the step-by-step guide for creating this type of project on this page.
The editor used in the template lets you add a drop-down list for labeling the selected object. See how to do this in the editor description (Dropdown list tab).
You can create a selection + drop-down list with category selection. See how to do this in the editor description (Dropdown list tab).
The coordinates are relative to the image.
In the standard template with an area selection editor, you can't use the control tasks, because in order for the assignment to be accepted by the system as correct, the object selected by the user must exactly match the control object. This is almost impossible. Therefore, you can leave the GOLDEN field empty in the task file or simply delete all the columns except INPUT.
In the standard template with an area selection editor, you can't use the control tasks, because in order for the assignment to be accepted by the system as correct, the object selected by the user must exactly match the control object. This is almost impossible. Therefore, you can leave the GOLDEN field empty in the task file or simply delete all the columns except INPUT.
You can't use training and the main pool with the Training type in an area selection project because for the response to be correct, the object selected by the user must exactly match the control object. This is almost impossible.
Such tasks are usually run with non-automatic acceptance: the performer submits an assignment, and then the assignment is rejected or accepted after the review.
For pre-selection of users, you can use “examination tasks”. Review the assignments and assign skills based on the percentage of accepted assignments. For this purpose, add the “Results of assignment review” rule to the pool. To make sure that only the good performers are admitted to the main pool, put a skill-based filter to the pool.
You can also edit the project so that the user sees 3 images at once and selects one of them.
You can structure your text classification task using the source text and radio buttons. It can also be text and checkboxes if you use multiple subjects.
We recommend that you take the “Text classification” template as a basis.
You can also create your own interface. All the available tools are described in the Requester's guide.
You can see how it's implemented in the “Transcript of audio recordings” template where a string-type output field is used. In the “Text recognition from an image” template, you can view how to describe text input fields. Please note that if you later want to use the Dawid-Skene aggregation method, you must use acceptable values.
You need to break down your task for Toloka. It's better if you split a 30-minute task intended for one person and containing all the phrases into individual phrases and give them to different performers. A template for such tasks doesn't require that the user installs a separate voice recorder app.
Refer to our step-by-step guide for creating a phrase recording task.
In the input data, you can pass the phrase for the performer to utter ("enable navigation"), and the speech speed (normal speed). This is the data you need to save to the TSV file. See the Guide to learn about creating a TSV file and its structure.
The preview contains 4 tasks per page by default. You can specify the number of tasks for your project when you upload the task file. Learn more about the preview.
For example, if you want one person to say the same phrase 10 times, create 10 tasks on your page. The cost is specified per page. To define how many people should utter a particular phrase, use the overlap in the pool. By the way, don't forget to set up filters in your pool. This way you can select only the performers who speak Russian and use mobile devices: client = mobile Toloka.
You can delegate review of the voice recordings to other performers by creating a separate project. Find brief instructions on how to do this here.
To the component that inserts the image, add the parameters: real-size=true and screenshot=true.
To create such a task, take the video markup template as a basis.
To host your videos on Yandex.Disk, connect Yandex.Disk and set up the project.
You can base it on the video markup template.
To host your videos on Yandex.Disk, connect Yandex.Disk and set up the project.
The survey includes an auxiliary input field. You can use it to pass any information, and it won't be visible to performers.
Upload one task and use the overlap parameter to enter the number of people you want to survey.
If your task contains many objects of different types, you should break it down. For example, you can ask users to select numbers in the first project, doorways and windows in the second project, walls in the third project, and plumbing in the fourth project.
The simpler the task, the cheaper it is and the better the quality of the final result. Set the cost of labeling a single class of objects in photos at about $0.01.
Use the Object selection in an image template. You can open this template in the editor and add a drop-down list for labeling the selected object. See how to do this in the editor description (Dropdown list tab).
You can use JavaScript to add assignment validation depending on a checkbox. An example is provided in the “Search for information online” template.
To open the camera instead of the gallery when the user taps the image upload button, in the Image upload button component specify camera=true.
In the mobile apps, performers can add photos from the default gallery (iOS) or Google photo (Android). To limit the capacity of adding online images, specify in the component requiredCoordinates=true. In this case, the system won't let the user add images without geotags.
