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@ -29,6 +29,7 @@
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- [Annotation with polylines](#annotation-with-polylines)
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- [Annotation with points](#annotation-with-points)
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- [Annotation with Auto Segmentation](#annotation-with-auto-segmentation)
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- [Auto annotation](#auto-annotation)
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- [Shape grouping](#shape-grouping)
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- [Filter](#filter)
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- [Analytics](#analytics)
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@ -135,7 +136,9 @@ Go to the [Django administration panel](http://localhost:8080/admin). There you
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**Use LFS**. If the annotation file is large, you can create a repository with
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[LFS](https://git-lfs.github.com/) support.
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**Source**. To create huge tasks please use ``shared`` server directory (choose ``Share`` option in the dialog).
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**Source**. Choose "Local" if you want to use files from your PC.
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Choose the "Remote" option if you want to use a one url-adress or a list.
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To create huge tasks please use shared server directory (choose "Share").
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**Z-Order**. Defines the order on drawn polygons. Check the box for enable layered displaying.
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@ -169,18 +172,36 @@ Go to the [Django administration panel](http://localhost:8080/admin). There you
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The option helps to load high resolution datasets faster.
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Use the value from ``1`` (completely compressed images) to ``95`` (almost not compressed images).
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**Select files**. Push this button to select files you want to annotate.
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**Frame Filter**. Use this option to filter video frames.
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For example, enter ``step=25`` to leave every twenty fifth frame in the video. Use this option on video files only.
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**Select files or URL list**. If you select `` Remote`` in `` Source``, you'll see a field where you can enter
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a list of URLs (one URL per line).
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Press `` Local`` or `` Share`` in the `` source`` field to choose some files
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for anotation from your local PC or a network folder respectively.
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Push ``Submit`` button and it will be added into the list of annotation tasks.
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Then, the created task will be displayed on dashboard:
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Then, the created task will be displayed on a dashboard:
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1. The Dashboard contains elements and each of them relates to a separate task. They are sorted in creation order.
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Each element contains: task name, preview, execution status, buttons, and one or more links.
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Each button is responsible for a specific function:
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- ``Dump Annotation`` — download an annotation file from the task (xml format)
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- ``Upload Annotation`` — upload an annotation file to the task (xml format)
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- ``Dump Annotation`` — download an annotation file from a task. Several formats are available:
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- [CVAT XML 1.1 for video](/cvat/apps/documentation/xml_format.md#interpolation)
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is highlighted if a task has the interpolation mode
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- [CVAT XML 1.1 for images](/cvat/apps/documentation/xml_format.md#annotation)
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is highlighted if a task has the annotation mode
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- [PASCAL VOC ZIP 1.0](http://host.robots.ox.ac.uk/pascal/VOC/)
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- [YOLO ZIP 1.0](https://pjreddie.com/darknet/yolo/)
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- [COCO JSON 1.0](http://cocodataset.org/#format-data)
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- ``MASK ZIP 1.0`` — archive contains a mask of each frame in the png format and a text file
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with the value of each color
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- [TFRecord ZIP 1.0](https://www.tensorflow.org/tutorials/load_data/tf_records)
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- ``Upload annotation`` is possible in same format as ``Dump annotation``, with exception of ``MASK ZIP 1.0``
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format and without choosing whether [CVAT XML 1.1](/cvat/apps/documentation/xml_format.md)
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refers to an image or video.
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- ``Update Task`` — bring up "Update task" panel. It is used to edit or add labels line
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- ``Delete Task`` — delete the task
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- ``Git Repository Sync`` — sync annotation with the dataset repository.
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@ -216,15 +237,28 @@ You can "register" a model and "use" it after that to pre annotate your tasks.
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The model manager allows you to manage your deep learning (DL) models uploaded for auto annotation.
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Using the functionality you can upload, update or delete a specific DL model.
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Use "Auto annotation" button to pre annotate a task using one of your DL models. [Read more](/cvat/apps/auto_annotation)
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Use "Auto annotation" button to pre annotate a task using one of your DL models.
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[Read more](/cvat/apps/auto_annotation)
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### Search
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There are several options how to use the search.
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It may be task's name, mode (annotation or interpolation), owner (username), assignee (username),
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status (annotation, validation, completed), id.
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- Search within all fields (owner, assignee, task name, task status, task mode).
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To execute enter a search string in search field.
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- Search for specific fields. How to perform:
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- ``owner: admin`` - all tasks created by the user who has the substring "admin" in his name
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- ``assignee: employee`` - all tasks which are assigned to a user who has the substring "employee" in his name
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- ``name: mighty`` - all tasks with the substring "mighty" in their names
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- ``mode: annotation`` or ``mode: interpolation`` - all tasks with images or videos.
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- ``status: annotation`` or ``status: validation`` or ``status: completed`` - search by status
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- ``id: 5`` - task with id = 5.
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- Multiple filters. Filters can be combined (except for the identifier) using the keyword `` AND``:
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- ``mode: interpolation AND owner: admin``
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- ``mode: annotation and status: annotation``
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The search is case insensitive.
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@ -274,7 +308,7 @@ And there is how they all look like:
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### Annotation mode (basics)
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Usage examples:
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@ -324,7 +358,7 @@ Usage examples:
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- Annotate a bounding box on the first frame for the object.
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- In ``Interpolation`` mode the bounding box will be interpolated on next frames automatically.
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1. If the object starts to change its position, you need to modify bounding
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boxes where it happens. It isn't necessary to change bounding boxes on each
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@ -337,7 +371,7 @@ Usage examples:
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- Let's jump 30 frames forward and adjust boundaries of the object.
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- After that, bounding boxes of the object between 630 and 660 frames
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will be changed automatically. For example, frame #645 looks like on the figure below:
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@ -403,18 +437,31 @@ Usage examples:
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### Downloading annotations
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1. To download the latest annotations, you have to save all changes first.
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Press ``Open Menu`` and then ``Save Work`` button. There is ``Ctrl+S``
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shortcut to save annotations quickly.
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To do this, click ``Open Menu`` button.
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1. After that, press ``Open Menu`` and then ``Dump Annotation`` button.
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1. After that, press ``Save Work`` button. There is ``Ctrl+S``
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shortcut to save annotations quickly.
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1. The annotation will be written into **.xml** file. To find the annotation
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file, you should go to the directory where your browser saves downloaded
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files by default. For more information visit [xml format page](/cvat/apps/documentation/xml_format.md).
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1. After that, press ``Dump Annotation`` button.
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1. Choose format dump annotation file. Dump annotation are available in several formats:
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- [CVAT XML 1.1 for video](/cvat/apps/documentation/xml_format.md#interpolation)
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is highlighted if a task has the interpolation mode
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- [CVAT XML 1.1 for images](/cvat/apps/documentation/xml_format.md#annotation)
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is highlighted if a task has the annotation mode
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- [PASCAL VOC ZIP 1.0](http://host.robots.ox.ac.uk/pascal/VOC/)
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- [YOLO ZIP 1.0](https://pjreddie.com/darknet/yolo/)
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- [COCO JSON 1.0](http://cocodataset.org/#format-data)
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- ``MASK ZIP 1.0`` — archive contains a mask of each frame in the png format and a text file with
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the value of each color
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- [TFRecord ZIP 1.0](https://www.tensorflow.org/tutorials/load_data/tf_records)
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### Task synchronization with a repository
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@ -900,6 +947,8 @@ automatically. You can adjust the polyline after it has been drawn.
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## Annotation with points
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### Points in annotation mode
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It is used for face landmarks annotation etc.
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Before starting, you have to be sure that ``Points`` is selected.
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@ -920,6 +969,32 @@ You can add/delete points after finishing.
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### Linear interpolation with one point
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You can use linear interpolation for points to annotate a moving object:
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1. Before starting, you have to be sure that ``Points`` is selected.
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1. Linear interpolation works only with one point, so you need to set ``Poly Shapes Size``: 1.
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1. After that select the interpolation mode.
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1. Press ``N`` or click ``Create Shape`` for entering drawing mode.
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Click LMB to create a point and shape will be automatically completed.
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1. Move forward a few frames and move the point to the desired position,
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this way you will create a keyframe and intermediate frames will be drawn automatically.
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You can work with this object as with an interpolated track: hide with help of ``Outside``,
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move around keyframes, etc.
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1. This way you'll get linear interpolation using `` Points``.
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## Annotation with Auto Segmentation
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Used to create a polygon semi-automatically. Before starting, you have to be
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@ -935,7 +1010,54 @@ in/out (when scrolling the mouse wheel) and move (when clicking the mouse
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wheel and moving the mouse) while drawing. At the end of Auto Segmentation,
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a shape is created and you can work with it as a polygon.
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## Auto annotation
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1. First you need to upload deep learning (DL) models using model manager.
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Only models in OpenVINO™ toolkit format are supported.
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If you would like to annotate a task with a custom model please convert it
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to the intermediate representation (IR) format via the model optimizer tool.
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See [OpenVINO documentation](https://software.intel.com/en-us/articles/OpenVINO-InferEngine) for details.
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1. Enter model name, and select model file using "Select files" button. To annotate a task with a custom model
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you need to prepare 4 files:
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- ``Model config`` (*.xml) - a text file with network configuration.
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- ``Model weights`` (*.bin) - a binary file with trained weights.
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- ``Label map`` (*.json) - a simple json file with label_map dictionary like an object with
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string values for label numbers.
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- ``Interpretation script`` (*.py) - a file used to convert net output layer to a predefined structure
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which can be processed by CVAT.
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More about creating model files can be found [here](/cvat/apps/auto_annotation).
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1. After downloading a model you have to create a task or find an already created one and
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click ``Run Auto Annotation`` button.
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1. In dialog window select a model you need. If it's necessary select the ``Delete current annotation`` checkbox.
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Adjust the labels so that the task labels will correspond to the labels of the DL model.
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Click ``Start`` to begin the auto annotatiton process.
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1. At runtime, you can see percentage of completion. You can also cancel the auto annotation
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process by clicking ``Cancel Auto Annotation``
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1. As a result, you will get an annotation with separate bounding boxes (or other shapes)
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1. Separated bounding boxes can be edited by removing false positives, adding unlabeled objects, and
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merging into tracks using ``Merge Shape``
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## Shape grouping
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@ -983,7 +1105,7 @@ In the trivial case, the correct filter must match the template: ``label[prop op
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``prop`` is a property which should be filtered. The following items are available:
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- ``id`` — identifier of an object. It helps to find a specific object easily
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in case of huge number of objects and static/documentation/images/frames.
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in case of huge number of objects and images or frames.
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- ``type`` — an annotation type. Possible values: ``annotation``, ``interpolation``
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- ``lock`` accepts ``true`` and ``false`` values. It can be used to hide all locked objects.
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- ``occluded`` accepts ``true`` and ``false`` values. It can be used to hide all occluded objects.
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TOsmanov
7 years ago
committed by
Nikita Manovich
