Usage
Navigate to the Categories tab found on the navigation bar, you will be presented with a create button. Here you can create as many categories as you would like.
Before we are able to annotate we must create a dataset with some categories. A Dataset contains images and is a way of separating different types of training data. If you would like more information about datasets or categories, you can click the blue information icon located beside the title.
To create a dataset start by clicking the green Create button located under Dataset tile. A popup with ask for a name as well as categories. Give it a unique name, and take note of the directory (found under Folder) and click Create Dataset.
Navigate to the datasets card click the Edit options found in the dropdown of the dataset card. Your category should be displayed in the categories window. From here you can change and select categories.
Once you click done you have added a category to the dataset and it should be displayed in the cards footer.
In this section we will be looking at using the file watcher methods to import images into a dataset. For windows users the process is slight different and a breif overver can be found here. While the annotator is running the datasets directory is being monitored for file events. Whenever an image is deleted, created or moved the corresponding event is reflected in the database.
Advantages:
- Easy to import large datasets
- No file size limit
- Simple
Disadvantages:
- Requires access to the machine running annotator
- Complicated for windows users
Navgivate to the datasets directroy located at the root of this project. Inside this folder you should see folders with the names of the datasets you have created. From here simply place images inside the corrsponding folder to add them to the dataset. Subfolders are highly recommended as they can be used as a filtering methods in the client UI.
The annotator will start adding the images to the dataset, give it a few seconds before refeshing the client.