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license: cc-by-4.0 |
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## HHD-Ethiopic Dataset |
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This dataset, named "HHD-Ethiopic," is designed for ethiopic text-image recognition tasks. It contains a collection of historical handwritten Manuscripts in the Ethiopic script. The dataset is intended to facilitate research and development for Ethiopic text-image recognition. |
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### Dataset Details/ |
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- __Size__: 79,684 <br> |
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- __Training Set__: 57,374 <br> |
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- __Test Set__: HHD-Ethiopic consists of two separate Test sets |
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- __Test Set I (IID)__: 6,375 images (randomly drawn from the training set) |
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- __Test Set II (OOD)__: 15,935 images (specifically from manuscripts dated in the 18th century) <br> |
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- __Validation Set__: 10% of the training set, randomly drawn <br> |
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- __Number of unique Ethiopic characters__ :306 |
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- __Dataset Formats__:the HHD-Ethiopic dataset is stored in two different formats to accommodate different use cases: |
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- __Raw Image and Ground-truth Text__: consistes of the original images and their corresponding ground-truth text. |
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The dataset is structured as raw images (.png) accompanied by a [train CSV file](https://huggingface.co/datasets/OCR-Ethiopic/HHD-Ethiopic/blob/main/train/train_raw/image_text_pairs_train.csv), [test-I CSV file](https://huggingface.co/datasets/OCR-Ethiopic/HHD-Ethiopic/blob/main/test/test_rand/image_text_pairs_test_rand.csv), and [test-II CSV file](https://huggingface.co/datasets/OCR-Ethiopic/HHD-Ethiopic/blob/main/test/test_18th/image_text_pairs_test_18th.csv) that contains the file names of the images and their respective ground-truth text for the training and two test sets respectively.<br> |
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-__Numpy Format__: in this format, both the images and the ground-truth text are stored in a convenient numpy format. The dataset provides pre-processed numpy arrays that can be directly used for training and testing models. |
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- __Metadata__(Human Level Performance ): we have also included metadata regarding the human-level performance predicted by individuals for the test sets. This metadata provides insights into the expected performance-level that humans can achieve in historical Ethiopic text-image recognition tasks. |
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- __Test Set I__ - for test set I, a group of 9 individuals was presented with a random subset of the dataset. They were asked to perform Ethiopic text-image recognition and provide their best efforts to transcribe the handwritten texts. The results were collected and stored in a CSV file, [Test-I-human_performance](https://github.com/bdu-birhanu/HHD-Ethiopic/blob/main/Dataset/human-level-predictions/6375_new_all.csv) included in the dataset. |
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- __Test Set II__ - Test set II which was prepared exclusively from Ethiopic historical handwritten documents dated in the 18th century. A different group of 4 individuals was given this subset for evaluation. The human-level performance predictions for this set are also stored in a separate CSV file, [Test-II_human_performance](https://github.com/bdu-birhanu/HHD-Ethiopic/blob/main/Dataset/human-level-predictions/15935_new_all.csv) |
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Please refer to the respective CSV files for detailed information on the human-level performance predictions. Each CSV file contains the necessary metadata, including the image filenames, groind-truth and the corresponding human-generated transcriptions. |
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If you would like to explore or analyze the human-level performance data further, please refer to the provided CSV files. |
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#### Citation |
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If you use the hhd-ethiopic dataset in your research, please consider citing it: |
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``` |
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@misc {author_2023, |
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author = { {Birhanu Hailu Belay, Isabelle Guyon, Tadele Mengiste, Bezawork Tilahun, Marcus Liwicki, Tesfa Tegegne, and Romain Egele}, |
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title = { HHD-Ethiopic:A Historical Handwritten Dataset for Ethiopic OCR with Baseline Models and Human-level Performance (Revision 50c1e04) }, |
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year = 2023, |
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url = { https://huggingface.co/datasets/OCR-Ethiopic/HHD-Ethiopic }, |
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doi = { 10.57967/hf/0691 }, |
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publisher = { Hugging Face } |
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} |
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``` |
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#### License |
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<a rel="license" href="http://creativecommons.org/licenses/by/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>. |
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