Annotation Points and Target

knowing how much data is being produced, and how productive annotators are, are important measures for running a project there are several metrics which are common in the industry, such as number of shapes or objects, the amount of properties set or tasks completed to normalize these measures across different projects and taxonomies kognic has developed a suite of productivity tools the basis for these tools is the annotation points specification and the annotation points target finding the configuration menu to setup annotation points and targets visit project settings , found under project management from there you should be able to see the annotation points tab select it and now you're able to use the annotation points configuration annotation points tab connection with the annotation instruction to be able to use the annotation points configuration, you need to have configured an annotation instruction for the project the annotation points configuration uses all the annotation instruction revisions that have been made during the project's lifecycle that means that you might see fields that don't exist within the currently used annotation instruction this is perfectly fine, and to be expected an ai allows for possibly multiple of the same geometries if you’ve configured an annotation instruction to use both 2d semantic segmentation, and 2d instance segmentation without having allow instances with multiple polygons checked then both of these will be merged into 2d segmentation annotation points specification each article that can be created in the kognic platform can be given an amount of annotation points that will be awarded the annotator adding them in a task these articles can be things like completing the task, finishing an object or setting properties below is an example of how a specification is applied to some annotator work to amount to a number of annotation points specification task 10p cuboid object 4p 2d bounding box object 2p task content cuboid objects 10 2d bounding box objects 7 annotation points = 10p 1 + 4p 10 + 2p 7 = 10 + 40 + 14 = 64p annotation points target to measure how productive an annotator is there needs to be a target which they are expected to reach the unit is annotation points per hour configuration the configuration allows for you to set the following values which then make up an entire annotation points specification annotation point target this is the total value of expected annotation points that the annotators are supposed to be meeting every hour annotation points target points per task this is how many annotation points a task should be given to the annotators upon submission of the task points per task points per geometry this is where you’re able to configure how many annotation points that should be rewarded for a specific geometry the fields that you’re able to set the values for are base points per object this is how many points an object should be rewarded additional points per shape how many points should be awarded per shape (object frames that the object lives in) points per geometry points per property you’re able to configure points per property for the object properties or scene properties that exist within the ai the values for dynamic properties are those that may change over time such as `occlusion`, whereas consistent properties are those that are consistent such as car points per property