datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
tibetan-page-orientation-classifier-dataset
Tibetan Page Orientation Dataset
Covers 7 Tibetan script families: Danyig, Druma, Gyuyig, Multi-Scripts, Pedri, Tsugdri, Uchen.
Dataset composition
Each manuscript page appears twice: once as the original scan (non_flipped) and once rotated 180° (flipped). The model's task is to distinguish these two orientations.
Scripts are balanced — each of the 7 script families contributes the same number of pages (downsampled to the smallest family).
Script (script)… See the full description on the dataset page: https://huggingface.co/datasets/BDRC/tibetan-page-orientation-classifier-dataset.solar-panel-orientationdocvqa-orientation-rlwds_vtab-dsprites_label_orientationcurriculum_1_docvqa_orientation_3999wds_dsprites_label_orientationZebrafish-AChE-Orientation-Classificationdoor_orientation
Dataset for training a door orientation detection model
Dataset description
This dataset contains raster images that show crops taken around detected doors.
The crops are squares of side the door length + a margin. One door => 2 crops.
At most one crop shows a door's quarter circle symbol.
There are 4 classes: double door, single door opening to the left, single door opening to the right, no arc (no door).
The crops were obtained with the code in… See the full description on the dataset page: https://huggingface.co/datasets/Rayonapp/door_orientation.document_orientation_datasetswds_vtab-dsprites_label_orientation_test
dSprites Orientation (Test set only)
Original paper: beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework
Homepage: https://github.com/deepmind/dsprites-dataset
Bibtex:
@misc{dsprites17,
author = {Loic Matthey and Irina Higgins and Demis Hassabis and Alexander Lerchner},
title = {dSprites: Disentanglement testing Sprites dataset},
howpublished= {https://github.com/deepmind/dsprites-dataset/},
year = "2017",
}
orientation_columns_dataset
About dataset
The main purpose of this dataset is to train and evaluate the model used for defining the orientation of the document and the number of text columns in it. As for the model, we chose EffecientNet B0. We constructed this dataset to represent the variety of documents we usually deal with. It contains open data in the form of scientific papers, legal acts, reports, tables, etc. The languages represented in this dataset are: Russian, English, French, Spanish, Portuguese… See the full description on the dataset page: https://huggingface.co/datasets/dedoc/orientation_columns_dataset.Egyptian_Hieroglyphic_Signs_Segmentation_with_Orientation
Egyptian Hieroglyphic Signs Segmentation with Orientation
Datasets for Ancient Egyptian Hieroglyphic Research
Egyptian Hieroglyphic Signs Segmentation with Orientation (SS) Dataset
Overview: The Signs Segmentation (SS) Dataset comprises 300 images, each containing a single line of ordered Ancient Egyptian hieroglyphic signs. These images were automatically cropped from segmented lines within the HLA Dataset using our trained layout analysis models. The SS… See the full description on the dataset page: https://huggingface.co/datasets/AhmedElTaher/Egyptian_Hieroglyphic_Signs_Segmentation_with_Orientation.vtab_dsprites_orientationvtab-1k_dsprites_orientation