datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
imagenet1k-256-wdsThis is imagenet1k in webdataset format. Images are stored as jpg files. Every image has been resized to a maximum side length of 256. That means that if an image in the original dataset was 1000 by 500, the new size will be 256 by 128. Images with a maximum side length of under 256 were not resized.
The total size of all dataset files is 57.8 GB, there are 1,281,167 rows in the training split and 50,000 rows in the validation split.
3D_Visual_Illusion_Depth_Estimation
3D Visual Illusion Depth Estimation Dataset
Dataset Summary
The 3D Visual Illusion Depth Estimation Dataset is designed for research on stereo and monocular depth estimation in 3D visual illusion scenes.It contains left and right stereo images, depth maps estimated from DepthAnything V2, and illusion-region masks.
Dataset Structure
Each sample in the dataset includes:
left: Left-view RGB image
right: Right-view RGB image
depth: Monocularly estimated depth… See the full description on the dataset page: https://huggingface.co/datasets/AdamYao/3D_Visual_Illusion_Depth_Estimation.nyu-depthv2-wds
Dataset Card for nyu-depthv2-wds
This is the NYU DepthV2 dataset, converted into the webdataset format. https://huggingface.co/datasets/sayakpaul/nyu_depth_v2/
There are 47584 samples in the training split, and 654 samples in the validation split.
I shuffled both the training samples, and the validation samples.
I also cropped 16 pixels from all sides of the image, and depth image. I did this because there is a white border around all images.
This is an example of the border… See the full description on the dataset page: https://huggingface.co/datasets/adams-story/nyu-depthv2-wds.