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isp-uv-es/IPL-SUIM-Grayscale-Illuminants

IPL-SUIM-Grayscale-Illuminants dataset Illuminant modified dataset version of the grayscale underwater semantic segmentation SUIM dataset. Dataset generation For each image, we first convert it to grayscale. Then, we generate a flat (constant) light spectrum and compute the pixel reflectances that obtain the RGM pixel values. Once we have the pixel reflectances, we generate different light spectrums of different dominant wavelengths (colors) and saturations and… See the full description on the dataset page: https://huggingface.co/datasets/isp-uv-es/IPL-SUIM-Grayscale-Illuminants.

sourceHugging Faceapache-2.0updated 4mo agoView on Hugging Face
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IPL-SUIM-Grayscale-Illuminants dataset

Illuminant modified dataset version of the grayscale underwater semantic segmentation SUIM dataset.

Dataset generation

For each image, we first convert it to grayscale. Then, we generate a flat (constant) light spectrum and compute the pixel reflectances that obtain the RGM pixel values. Once we have the pixel reflectances, we generate different light spectrums of different dominant wavelengths (colors) and saturations and compute the new modified images. We apply the method to 100 Cityscapes images. For each original image we generate 120 modified versions (20 colors and 6 saturations).

Dataset structure

The originalimages folder contains the original 110 grayscale SUIM images. The modifiedimages folder have 110 subfolders from image1 to image110. Each subfolder has the 120 modified images for each original image. Modified images are named as imagenameXtonoTsatS.png, where X is the image index from 1 to 100, T is the color index from 1 to 20 and S is the saturation index from 1 to 6. Labels (i.e. segmentation masks) can be obtained from the original SUIM dataset.