The provided dataset consists of:

• 300 synthetic images featuring water-sensitive paper ()
• 2 real water-sensitive paper images manually annotated
• 127 real water-sensitive paper images, divided into squares, pre-annotated

The synthetic dataset was generated using an automated algorithm that creates individual droplets and positions them against a yellow artificial background. Annotations for instance segmentation each droplet are stored in a text file formatted according to YOLOv8 annotation format.

Some key features include:

• Distribution of number of droplets per image: the number of droplets per image is determined
  based on the configuration values to follow a normal distribution.
• Size distribution of droplets: the algorithm calculates the size of each droplet based on the
  Rosin-Rammler distribution.
• Image Resolution: images were created with three different resolutions
• Yellow Background: the background of each image is composed by a yellow radial gradient generated for each water-sensitive paperimage. The gradient transitions between two randomly chosen tones of yellow from a list of shades of yellow taken from real images of water-sensitive paper.
• Droplet Color: the colors of the droplets are taken from two distinct real datasets of water-sensitive paper.
• Droplet Shape: the shapes of the droplets are selected from a list containing 25 404 shapes, which are taken from real water-sensitive paper images.

Each set of images of this dataset is organized into two folder:

1. image: contains the water-sensitive paper images
2. label: contains the labels in YOLOv8 polygon format of each one of the droplets in the image

The dataset consists of 300 synthetic images featuring water-sensitive paper. It was generated using an automated algorithm that creates individual droplets and positions them against a yellow artificial background. Annotations for instance segmentation each droplet are stored in a text file formatted according to YOLOv8 annotation format.

Some key features include:

• Distribution of number of droplets per image: the number of droplets per image is determined
  based on the configuration values to follow a normal distribution.
• Size distribution of droplets: the algorithm calculates the size of each droplet based on the
  Rosin-Rammler distribution.
• Image Resolution: images were created with three different resolutions
• Yellow Background: the background of each image is composed by a yellow radial gradient generated for each water-sensitive paperimage. The gradient transitions between two randomly chosen tones of yellow from a list of shades of yellow taken from real images of water-sensitive paper.
• Droplet Color: the colors of the droplets are taken from two distinct real datasets of water-sensitive paper.
• Droplet Shape: the shapes of the droplets are selected from a list containing 25 404 shapes, which are taken from real water-sensitive paper images.

The dataset is organized in two folder:

1. image: contains each one of the water-sensitive paper images
2. label: contains the labels in YOLOv8 polygon format of each one of the droplets in the image