Polygon Annotation Case Study

Polygon Data Annotation

There are many items in irregular shapes that 2D bounding boxes cannot accurately recognize. However, polygon data annotation can label curves and different angles, more accurately reflecting the real shape of the target.

In the field of data annotation, the level of machine models depends on data accuracy. Therefore, the polygon data annotation tool is the best way to ensure pixel-level accuracy of training data.

Applied Fields

Generally, polygon data annotation is applied in robot capturing, medical image recognition, satellite image recognition, and irregular objects in urban landscapes, such as vehicles, trees, and pools.

Polygon Project on Fishes

Communication with clients

1 For the truncation part, should we label it or not?

2 For the labeling requirement below, which one works for you?

i. Only the fish with 100% visibility(including fins) need to be labeled.

ii. The fish with general outline need to be labeled( fins can be excluded as they are always covered by other things)

iii. The fish with above 50% visibility need to be labeled. (The percentage can be changed)

3 We would like to know the density of fish per image

i. under 10

ii. 10–20

iii. above 20

4 Accuracy level: labeling down to 5 pixels ( or any other requirement)

Annotation Requirements

1 The polygon borders match the outline of the subject completely including the subject

2 If a task contains multiple subjects that need to be annotated with polygons, each subject should be done so respectively

3 The invisible parts of the target should also be marked

4 No polygons missing, no incomplete polygons, and no incorrect polygons

End

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