Annotation Points

annotation points (ap) overview what are annotation points? annotation points (ap) are a project level scoring system that quantifies every annotation action—tasks, objects, shapes, and properties—into a single, normalized unit for setting ap see our annotation points & targets https //docs kognic com/annotation points and target guide for details 1\ why use ap? normalize effort different projects and taxonomies vary in complexity; ap lets you compare “apples to apples ” set clear targets define an ap/hour goal per project and track productivity as a percentage of that target align on value reward high effort work (3d boxes, property setting etc ) and discourage low value work such as micro adjustments 2\ how is ap calculated? ap calculation formula ap = (points per task × #tasks) \+ ∑\[points per object × #objects] \+ ∑\[points per shape × #total shapes] \+ ∑\[points per property × #properties] \+ ∑\[points per dynamic shape × (#total shapes #static shapes)] \+ ∑\[points per static object × #static objects] points per task flat bonus for submitting a task points per object base points for creating each object points per shape additional points per frame/shape instance points per property points for setting or updating object/scene properties points per static objects points for setting or updating a static object points per dynamic object points for setting or updating a dynamic object ap are only generated during annotation and correction tasks (not pure reviews) actual ap appear in parentheses next to your productivity percentage ap targets & productivity % once your project’s ap specification is configured, set an hourly ap target (e g 300 ap/h) productivity is then productivity (%) = (total ap earned ÷ (target ap/h × hours worked)) × 100 🟢 ≥ 100% meeting or exceeding target 🔴 < 100% below target stopwatch reported hours are used for “hours worked ” if no stopwatch data exists, productivity shows as n/a in addition to the overall ap/hour target, projects can configure an expected learning curve — a per week speed ramp up expressed as a percentage of the annotation speed target this is used on the learning curve metrics tab to visualize whether new annotators are onboarding at the expected pace see annotation points and target for configuration details 3\ faqs q why did my ap drop, or even go negative when i added shapes? a our system takes a “snapshot” of your total ap every 10 minutes and recalculates the entire annotation chain using the current point weights if the project manager have recently lowered the points per object/shape, the snapshot will apply the new lower weights retroactively to all previously annotated shapes compare that new total against your last snapshot if the new weights are lower than before, your historic ap total shrinks—so adding shapes can produce a negative delta in ap