Automate image annotations with CVAT on Onepanel.
Computer Vision Annotation Tool (CVAT) is an open source tool for annotating digital images and videos. The main function of the application is to provide users with convenient annotation instruments. For that purpose, we designed CVAT as a versatile service that has many powerful features.
CVAT is a browser-based application for both individuals and teams that supports different work scenarios. The main tasks of supervised machine learning can be divided into three groups:
- Object detection
- Image classification
- Image segmentation
CVAT is Embedded into Oneapanel and can be used for annotations in a single click.
Let’s Walk Through a running a simple annotation task in CVAT on Onepanel.io
Data annotation
Data annotation in CVAT starts by creating an annotation task with the following instructions:
- Name a task
- Specify labels and their attributes
- Choose files to download
Datasets are loaded from the local file system or a mounted file system inside a container. A task can include one image archive, one video, a set or catalogue of images from shared storage.
- A few additional options:
- Bug Tracker : To specify the full URL of a detailed annotation specification and other additional information.
- Dataset Repository: To specify the URL of a Git-repository for data storage.
- Flip Images : To rotate all images 180 degrees.
- Z-Order : To support the layers for a segmentation task .
- Segment Size : To divide a huge dataset into a few smaller segments .
- Overlap : To make overlapped segments . This option makes video continuous from one segment into another
- Image Quality : To specify the quality of uploaded images .
Then press Submit button and it will be added into the list of annotation tasks.
Each link inside the Jobs section corresponds to one segment. In this case, the dataset isn’t divided into segments. Users can follow any link to start the annotation process.
Users can use four shapes to annotate images: boxes, polygons (generally, for segmentation tasks), polylines (which can be useful for annotating roadmarks), and points (e.g., for annotating face landmarks or pose estimation).
Additionally, there are many features for use in typical annotation tasks: automation instruments (copy and propagate objects, interpolation, and automatic annotation using the TensorFlow OD API), visual settings, shortcuts, filters, and others. These can be changed in the Settings menu.
The Help menu also contains a number of shortcuts and other hints.
The annotation process is detailed in the examples below
Interpolation mode: CVAT may be used to interpolate bounding boxes and attributes between key frames. Then a set of images will be annotated automatically.
Attribute annotation mode: Attribute Annotation Mode was developed for image classification and accelerates the process of attribute annotation by focusing the annotator’s attention on just one exact attribute. Additionally, the process of annotation is carried out in this mode by using hot keys.
Segmentation mode: Annotation with polygons is used for semantic segmentation and instance segmentation. In this mode, visual settings make the annotation process easier.
Downloading annotations
Users have to choose Dump Annotation to download the latest annotations. It will be written in .xml file that contains some metadata and all annotations. If a user connected a Git repository at the stage of creating a task, this file can be downloaded there.
You can use the default tf_annotations models or upload your own to pre-load bounding boxes directly within CVAT.
Customizing the Tensorflow model in CVAT
You can now change the model used when Run TF Annotation button is pressed by downloading your custom models into the /onepanel/input/models directory.
You will need to ensure that you add the class file ( *.csv) and the tensorflow frozen model file (*.pb). The class file contains the classes associated with the frozen model.
You can also find the complete instructions for the open source version of CVAT here: CVAT Github docs
Read How to train neural network on Onepanel here.
Try the CVAT GPU Optimized Demo here.
