cityscapes
mask2former-swin-large-cityscapes-semanticoneformer_cityscapes_swin_largesegformer-b5-finetuned-cityscapes-1024-1024segformer-b0-finetuned-cityscapes-1024-1024segformer-b2-finetuned-cityscapes-1024-1024segformer-b0-finetuned-cityscapes-512-1024mask2former-swin-tiny-cityscapes-semanticsegformer-b0-finetuned-cityscapes-640-1280
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IPL-Cityscapes-Illuminants
IPL-CityscapesIlluminants-dataset
Illuminant modified dataset version of the famous autonomous driving semantic segmentation Cityscapes dataset.
Dataset generation
For each image, 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… See the full description on the dataset page: https://huggingface.co/datasets/isp-uv-es/IPL-Cityscapes-Illuminants.IPL-Cityscapes-LuminanceContrasts
IPL-CityscapesLuminanceContrasts-dataset
Controled luminance and contrasts modified dataset version of the famous autonomous driving semantic segmentation Cityscapes dataset.
Dataset generation
For each original image, we convert it to ATD color space. Once in this space, we compute its mean luminance, achromatic contrast and chromatic contast. We modify each of its characteristics in turns from 0.5 to 1.5 of its original value. Then we return the image to RGB space. We… See the full description on the dataset page: https://huggingface.co/datasets/isp-uv-es/IPL-Cityscapes-LuminanceContrasts.cityscapesTTA-Cityscapes-Ccityscapes_segmentation