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+---
+title: 'Annotation quality & Honeypot'
+linkTitle: 'Annotation quality'
+weight: 14
+description: 'How to check the quality of annotation in CVAT'
+---
+
+In CVAT, it's possible to evaluate the quality of annotation through
+the creation of a **Ground truth** job, referred to as a Honeypot.
+To estimate the task quality, CVAT compares all other jobs in the task against the
+established **Ground truth** job, and calculates annotation quality
+based on this comparison.
+
+> **Note** that quality estimation only supports
+> 2d tasks. It supports all the annotation types except 2d cuboids.
+
+> **Note** that tracks are considered separate shapes
+> and compared on a per-frame basis with other tracks and shapes.
+
+See:
+
+- [Ground truth job](#ground-truth-job)
+- [Managing Ground Truth jobs: Import, Export, and Deletion](#managing-ground-truth-jobs-import-export-and-deletion)
+ - [Import](#import)
+ - [Export](#export)
+ - [Delete](#delete)
+- [Assessing data quality with Ground truth jobs](#assessing-data-quality-with-ground-truth-jobs)
+ - [Quality data](#quality-data)
+ - [Annotation quality settings](#annotation-quality-settings)
+ - [GT conflicts in the CVAT interface](#gt-conflicts-in-the-cvat-interface)
+- [Annotation quality \& Honeypot video tutorial](#annotation-quality--honeypot-video-tutorial)
+
+## Ground truth job
+
+A **Ground truth** job is a way to tell CVAT where to store
+and get the "correct" annotations for task quality estimation.
+
+To estimate task quality, you need to
+create a **Ground truth** job in the task,
+and annotate it. You don’t need to
+annotate the whole dataset twice,
+the annotation quality of a small part of
+the data shows the quality of annotation for
+the whole dataset.
+
+For the quality assurance to function correctly, the **Ground truth** job must
+have a small portion of the task frames and the frames must be chosen randomly.
+Depending on the dataset size and task complexity,
+**5-15% of the data is typically good enough** for quality estimation,
+while keeping extra annotation overhead acceptable.
+
+For example, in a typical **task with 2000 frames**, selecting **just 5%**,
+which is 100 extra frames to annotate, **is enough** to estimate the
+annotation quality. If the task contains **only 30 frames**, it's advisable to
+select **8-10 frames**, which is **about 30%**.
+
+It is more than 15% but in the case of smaller datasets,
+we need more samples to estimate quality reliably.
+
+To create a **Ground truth** job, do the following:
+
+1. Create a [task](/docs/manual/basics/create_an_annotation_task/), and open the task page.
+2. Click **+**.
+
+ 
+
+3. In the **Add new job** window, fill in the following fields:
+
+ 
+
+ - **Job type**: Use the default parameter **Ground truth**.
+ - **Frame selection method**: Use the default parameter **Random**.
+ - **Quantity %**: Set the desired percentage of frames for the **Ground truth** job.
+ **Note** that when you use **Quantity %**, the **Frames** field will be autofilled.
+ - **Frame count**: Set the desired number of frames for the "ground truth" job.
+ **Note** that when you use **Frames**, the **Quantity %** field will be will be autofilled.
+ - **Seed**: (Optional) If you need to make the random selection reproducible, specify this number.
+ It can be any integer number, the same value will yield the same random selection (given that the
+ frame number is unchanged). **Note** that if you want to use a
+ custom frame sequence, you can do this using the server API instead,
+ see [Jobs API #create](https://opencv.github.io/cvat/docs/api_sdk/sdk/reference/apis/jobs-api/#create).
+
+4. Click **Submit**.
+5. Annotate frames, save your work.
+6. Change the status of the job to **Completed**.
+7. Change **Stage** to **Accepted**.
+
+The **Ground truth** job will appear in the jobs list.
+
+
+
+## Managing Ground Truth jobs: Import, Export, and Deletion
+
+Annotations from **Ground truth** jobs are not included in the dataset export,
+they also cannot be imported during task annotations import
+or with automatic annotation for the task.
+
+Import, export, and delete options are available from the
+job's menu.
+
+
+
+### Import
+
+If you want to import annotations into the **Ground truth** job, do the following.
+
+1. Open the task, and find the **Ground truth** job in the jobs list.
+2. Click on three dots to open the menu.
+3. From the menu, select **Import annotations**.
+4. Select import format, and select file.
+5. Click **OK**.
+
+> **Note** that if there are imported annotations for the frames that exist in the task,
+> but are not included in the **Ground truth** job, they will be ignored.
+> This way, you don't need to worry about "cleaning up" your **Ground truth**
+> annotations for the whole dataset before importing them.
+> Importing annotations for the frames that are not known in the task still raises errors.
+
+### Export
+
+To export annotations from the **Ground truth** job, do the following.
+
+1. Open the task, and find a job in the jobs list.
+2. Click on three dots to open the menu.
+3. From the menu, select **Export annotations**.
+
+### Delete
+
+To delete the **Ground truth** job, do the following.
+
+1. Open the task, and find the **Ground truth** job in the jobs list.
+2. Click on three dots to open the menu.
+3. From the menu, select **Delete**.
+
+## Assessing data quality with Ground truth jobs
+
+Once you've established the **Ground truth** job, proceed to annotate the dataset.
+
+CVAT will begin the quality comparison between the annotated task and the
+**Ground truth** job in this task once it is finished (on the `acceptance` stage and in the `completed` state).
+
+> **Note** that the process of quality calculation may take up to several hours, depending on
+> the amount of data and labeled objects, and is **not updated immediately** after task updates.
+
+To view results go to the **Task** > **Actions** > **View analytics**> **Performance** tab.
+
+
+
+### Quality data
+
+The Analytics page has the following fields:
+
+
+
+| Field | Description |
+| ----------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| Mean annotation quality | Displays the average quality of annotations, which includes: the count of accurate annotations, total task annotations, ground truth annotations, accuracy rate, precision rate, and recall rate. |
+| GT Conflicts | Conflicts identified during quality assessment, including extra or missing annotations. Mouse over the **?** icon for a detailed conflict report on your dataset. |
+| Issues | Number of [opened issues](/docs/manual/advanced/review/). If no issues were reported, will show 0. |
+| Quality report | Quality report in JSON format. |
+| Ground truth job data | "Information about ground truth job, including date, time, and number of issues. |
+| List of jobs | List of all the jobs in the task |
+
+
+
+### Annotation quality settings
+
+If you need to tweak some aspects of comparisons, you can do this from
+the **Annotation Quality Settings** menu.
+
+You can configure what overlap
+should be considered low or how annotations must be compared.
+
+The updated settings will take effect
+on the next quality update.
+
+To open **Annotation Quality Settings**, find
+**Quality report** and on the right side of it, click on
+three dots.
+
+The following window will open.
+Hover over the **?** marks to understand what each field represents.
+
+
+
+Annotation quality settings have the following parameters:
+
+
+
+| Field | Description |
+| ---------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| Min overlap threshold | Min overlap threshold(IoU) is used for the distinction between matched / unmatched shapes. |
+| Low overlap threshold | Low overlap threshold is used for the distinction between strong/weak (low overlap) matches. |
+| OKS Sigma | IoU threshold for points. The percent of the box area, used as the radius of the circle around the GT point, where the checked point is expected to be. |
+| Relative thickness (frame side %) | Thickness of polylines, relative to the (image area) ^ 0.5. The distance to the boundary around the GT line inside of which the checked line points should be. |
+| Check orientation | Indicates that polylines have direction. |
+| Min similarity gain (%) | The minimal gain in the GT IoU between the given and reversed line directions to consider the line inverted. Only useful with the Check orientation parameter. |
+| Compare groups | Enables or disables annotation group checks. |
+| Min group match threshold | Minimal IoU for groups to be considered matching, used when the Compare groups are enabled. |
+| Check object visibility | Check for partially-covered annotations. Masks and polygons will be compared to each other. |
+| Min visibility threshold | Minimal visible area percent of the spatial annotations (polygons, masks) |
+| For reporting covered annotations, useful with the Check object visibility option. |
+| Match only visible parts | Use only the visible part of the masks and polygons in comparisons. |
+
+
+
+### GT conflicts in the CVAT interface
+
+To see GT Conflicts in the CVAT interface, go to **Review** >
+**Issues** > **Show ground truth annotations and conflicts**.
+
+
+
+The ground truth (GT) annotation is depicted as
+a dotted-line box with an associated label.
+
+Upon hovering over an issue on the right-side panel with your mouse,
+the corresponding GT Annotation gets highlighted.
+
+Use arrows in the Issue toolbar to move between GT conflicts.
+
+To create an issue related to the conflict,
+right-click on the bounding box and from the
+menu select the type of issue you want to create.
+
+
+
+## Annotation quality & Honeypot video tutorial
+
+This video demonstrates the process:
+
+
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