diff --git a/cvat/apps/documentation/static/documentation/images/image100.jpg b/cvat/apps/documentation/static/documentation/images/image100.jpg deleted file mode 100644 index 544166126eb..00000000000 Binary files a/cvat/apps/documentation/static/documentation/images/image100.jpg and /dev/null differ diff --git a/cvat/apps/documentation/static/documentation/images/image100_DETRAC.jpg b/cvat/apps/documentation/static/documentation/images/image100_DETRAC.jpg new file mode 100644 index 00000000000..3865a734fdc Binary files /dev/null and b/cvat/apps/documentation/static/documentation/images/image100_DETRAC.jpg differ diff --git a/cvat/apps/documentation/static/documentation/images/image113.jpg b/cvat/apps/documentation/static/documentation/images/image113.jpg deleted file mode 100644 index 8fe6b35b7fc..00000000000 Binary files a/cvat/apps/documentation/static/documentation/images/image113.jpg and /dev/null differ diff --git a/cvat/apps/documentation/static/documentation/images/image113_DETRAC.jpg b/cvat/apps/documentation/static/documentation/images/image113_DETRAC.jpg new file mode 100644 index 00000000000..4002a4a73ef Binary files /dev/null and b/cvat/apps/documentation/static/documentation/images/image113_DETRAC.jpg differ diff --git a/cvat/apps/documentation/static/documentation/images/image119.jpg b/cvat/apps/documentation/static/documentation/images/image119.jpg deleted file mode 100644 index 6cddfc1c56f..00000000000 Binary files a/cvat/apps/documentation/static/documentation/images/image119.jpg and /dev/null differ diff --git a/cvat/apps/documentation/static/documentation/images/image119_DETRAC.jpg b/cvat/apps/documentation/static/documentation/images/image119_DETRAC.jpg new file mode 100644 index 00000000000..8689dd8665e Binary files /dev/null and b/cvat/apps/documentation/static/documentation/images/image119_DETRAC.jpg differ diff --git a/cvat/apps/documentation/static/documentation/images/image120.jpg b/cvat/apps/documentation/static/documentation/images/image120.jpg index 225cf7e63fb..41f47134b61 100644 Binary files a/cvat/apps/documentation/static/documentation/images/image120.jpg and b/cvat/apps/documentation/static/documentation/images/image120.jpg differ diff --git a/cvat/apps/documentation/static/documentation/images/image121.jpg b/cvat/apps/documentation/static/documentation/images/image121.jpg deleted file mode 100644 index 20ee4a73dae..00000000000 Binary files a/cvat/apps/documentation/static/documentation/images/image121.jpg and /dev/null differ diff --git a/cvat/apps/documentation/static/documentation/images/image121_DETRAC.jpg b/cvat/apps/documentation/static/documentation/images/image121_DETRAC.jpg new file mode 100644 index 00000000000..0f30ce46a70 Binary files /dev/null and b/cvat/apps/documentation/static/documentation/images/image121_DETRAC.jpg differ diff --git a/cvat/apps/documentation/static/documentation/images/image133.JPG b/cvat/apps/documentation/static/documentation/images/image133.JPG new file mode 100644 index 00000000000..70be971530f Binary files /dev/null and b/cvat/apps/documentation/static/documentation/images/image133.JPG differ diff --git a/cvat/apps/documentation/user_guide.md b/cvat/apps/documentation/user_guide.md index 1f2320871a1..939ae067267 100644 --- a/cvat/apps/documentation/user_guide.md +++ b/cvat/apps/documentation/user_guide.md @@ -31,7 +31,7 @@ - [Points in annotation mode](#points-in-annotation-mode) - [Linear interpolation with one point](#linear-interpolation-with-one-point) - [Annotation with Auto Segmentation](#annotation-with-auto-segmentation) - - [Auto annotation](#auto-annotation) + - [Automatic annotation](#auto-annotation) - [Shape grouping](#shape-grouping) - [Filter](#filter) - [Analytics](#analytics) @@ -1078,50 +1078,47 @@ a shape is created and you can work with it as a polygon. ![](static/documentation/images/gif009_DETRAC.gif) -## Auto annotation +## Automatic annotation -1. First you need to upload deep learning (DL) models using model manager. - Only models in OpenVINO™ toolkit format are supported. - If you would like to annotate a task with a custom model please convert it - to the intermediate representation (IR) format via the model optimizer tool. - See [OpenVINO documentation](https://software.intel.com/en-us/articles/OpenVINO-InferEngine) for details. +Automatic Annotation is used for creating preliminary annotations. +To use Automatic Annotation you need a DL model. You can use primary models or models uploaded by a user. +You can find the list of available models in the ``Models`` section. - ![](static/documentation/images/image099.jpg) +1. To launch automatic annotation, you should open the dashboard and find a task which you want to annotate. + Then click the ``Actions`` button and choose option ``Automatic Annotation`` from the dropdown menu. -1. Enter model name, and select model file using "Select files" button. To annotate a task with a custom model - you need to prepare 4 files: - - ``Model config`` (*.xml) - a text file with network configuration. - - ``Model weights`` (*.bin) - a binary file with trained weights. - - ``Label map`` (*.json) - a simple json file with label_map dictionary like an object with - string values for label numbers. - - ``Interpretation script`` (*.py) - a file used to convert net output layer to a predefined structure - which can be processed by CVAT. - More about creating model files can be found [here](/cvat/apps/auto_annotation). + ![](static/documentation/images/image119_DETRAC.jpg) - ![](static/documentation/images/image104.jpg) - -1. After downloading a model you have to create a task or find an already created one and - click ``Run Auto Annotation`` button. - - ![](static/documentation/images/image119.jpg) - -1. In dialog window select a model you need. If it's necessary select the ``Delete current annotation`` checkbox. - Adjust the labels so that the task labels will correspond to the labels of the DL model. - Click ``Start`` to begin the auto annotatiton process. +1. In the dialog window select a model you need. DL models are created for specific labels, e.g. + the Crossroad model was taught using footage from cameras located above the highway and it is best to + use this model for the tasks with similar camera angles. + If it's necessary select the ``Clean old annotations`` checkbox. + Adjust the labels so that the task labels will correspond to the labels of the DL model. + For example, let’s consider a task where you have to annotate labels “car” and “person”. + You should connect the “person” label from the model to the “person” label in the task. + As for the “car” label, you should choose the most fitting label available in the model - the “vehicle” label. + The task requires to annotate cars only and choosing the “vehicle” label implies annotation of all vehicles, + in this case using auto annotation will help you complete the task faster. + Click ``Submit`` to begin the automatic annotation process. ![](static/documentation/images/image120.jpg) -1. At runtime, you can see percentage of completion. You can also cancel the auto annotation - process by clicking ``Cancel Auto Annotation`` +1. At runtime, you can see the percentage of completion. - ![](static/documentation/images/image121.jpg) + ![](static/documentation/images/image121_DETRAC.jpg) 1. As a result, you will get an annotation with separate bounding boxes (or other shapes) ![](static/documentation/images/gif014_DETRAC.gif) -1. Separated bounding boxes can be edited by removing false positives, adding unlabeled objects, and - merging into tracks using ``Merge Shape`` +1. Separated bounding boxes can be edited by removing false positives, adding unlabeled objects and + merging into tracks using ``ReID merge`` function. Click the ``ReID merge`` button in the menu. + You can use the default settings (for more information click [here](cvat/apps/reid/README.md)). + To launch the merging process click ``Merge``. Each frame of the track will be a key frame. + + ![](static/documentation/images/image133.jpg) + +1. You can remove false positives and edit tracks using ``Split`` and ``Merge`` functions. ![](static/documentation/images/gif015_DETRAC.gif) @@ -1216,7 +1213,7 @@ If your CVAT instance is created with analytics support, you can press the "analytics" button in dashboard, a new tab with analytics and journals will be opened. -![](static/documentation/images/image113.jpg) +![](static/documentation/images/image113_DETRAC.jpg) It allows you to see how much working time every user spend on each task and how much they did, over any time range.