# ***** BN-HTRd Splitted Dataset for Experimentation *****

# <u>Original Dataset:</u> "BN-HTRd: A Benchmark Dataset for Document Level Offline Bangla Handwritten Text Recognition (HTR)"
Link: https://data.mendeley.com/datasets/743k6dm543

### Description
We introduce a new dataset for offline Handwritten Text Recognition (HTR) from images of Bangla scripts comprising words, lines, and document-level annotations. The BN-HTRd dataset is based on the BBC Bangla News corpus - which acted as ground truth texts for the handwritings. Our dataset contains a total of 786 full-page images collected from 150 different writers. With a staggering 108,147 instances of handwritten words, distributed over 13,867 lines and 23,115 unique words, this is currently the 'largest and most comprehensive dataset' in this field. We also provided the bounding box annotations (YOLO format) for the segmentation of words/lines and the ground truth annotations for full-text, along with the segmented images and their positions. The contents of our dataset came from a diverse news category, and annotators of different ages, genders, and backgrounds, having variability in writing styles. The BN-HTRd dataset can be adopted as a basis for various handwriting classification tasks such as end-to-end document recognition, word-spotting, word/line segmentation, and so on. 

The statistics of the original dataset are given below:

Number of writers = 150\
Total number of images = 786\
Total number of lines = 14,383\
Total number of words = 1,08,181\
Total number of unique words = 23,115\
Total number of punctuation = 7,446\
Total number of characters = 5,74,203\


### Steps to reproduce
See the Paper: https://arxiv.org/abs/2206.08977

 #### Paper Information for Citation
 ```ruby
 @misc{https://doi.org/10.48550/arxiv.2206.08977,
  doi = {10.48550/ARXIV.2206.08977},
  url = {https://arxiv.org/abs/2206.08977},
  author = {Rahman, Md. Ataur and Tabassum, Nazifa and Paul, Mitu and Pal, Riya and Islam, Mohammad Khairul},
  title = {BN-HTRd: A Benchmark Dataset for Document Level Offline Bangla Handwritten Text Recognition (HTR) and Line Segmentation},
  publisher = {arXiv},
  year = {2022},
  copyright = {arXiv.org perpetual, non-exclusive license}
}
```
task_categories:image-segmentation task_categories:image-to-text size_categories:10K<n<100K language:bn license:cc-by-4.0 Handwriting Recognition Document Imaging Annotation Image Segmentation Bengali Language Word Spotting arxiv:2206.08977 doi:10.57967/hf/0546 region:us
{"language": ["bn"], "license": "cc-by-4.0", "size_categories": ["10K<n<100K"], "task_categories": ["image-segmentation", "image-to-text"], "pretty_name": "BN-HTRd Splitted Dataset for Experimentation", "tags": ["Handwriting Recognition", "Document Imaging", "Annotation", "Image Segmentation", "Bengali Language", "Word Spotting"]}
TAGS
#task_categories-image-segmentation #task_categories-image-to-text #size_categories-10K<n<100K #language-Bengali #license-cc-by-4.0 #Handwriting Recognition #Document Imaging #Annotation #Image Segmentation #Bengali Language #Word Spotting #arxiv-2206.08977 #doi-10.57967/hf/0546 #region-us 

# * BN-HTRd Splitted Dataset for Experimentation *

# <u>Original Dataset:</u> "BN-HTRd: A Benchmark Dataset for Document Level Offline Bangla Handwritten Text Recognition (HTR)"
Link: URL

### Description
We introduce a new dataset for offline Handwritten Text Recognition (HTR) from images of Bangla scripts comprising words, lines, and document-level annotations. The BN-HTRd dataset is based on the BBC Bangla News corpus - which acted as ground truth texts for the handwritings. Our dataset contains a total of 786 full-page images collected from 150 different writers. With a staggering 108,147 instances of handwritten words, distributed over 13,867 lines and 23,115 unique words, this is currently the 'largest and most comprehensive dataset' in this field. We also provided the bounding box annotations (YOLO format) for the segmentation of words/lines and the ground truth annotations for full-text, along with the segmented images and their positions. The contents of our dataset came from a diverse news category, and annotators of different ages, genders, and backgrounds, having variability in writing styles. The BN-HTRd dataset can be adopted as a basis for various handwriting classification tasks such as end-to-end document recognition, word-spotting, word/line segmentation, and so on. 

The statistics of the original dataset are given below:

Number of writers = 150\
Total number of images = 786\
Total number of lines = 14,383\
Total number of words = 1,08,181\
Total number of unique words = 23,115\
Total number of punctuation = 7,446\
Total number of characters = 5,74,203\


### Steps to reproduce
See the Paper: URL

 #### Paper Information for Citation
 
# * BN-HTRd Splitted Dataset for Experimentation * # <u>Original Dataset:</u> "BN-HTRd: A Benchmark Dataset for Document Level Offline Bangla Handwritten Text Recognition (HTR)"
Link: URL ### Description
We introduce a new dataset for offline Handwritten Text Recognition (HTR) from images of Bangla scripts comprising words, lines, and document-level annotations. The BN-HTRd dataset is based on the BBC Bangla News corpus - which acted as ground truth texts for the handwritings. Our dataset contains a total of 786 full-page images collected from 150 different writers. With a staggering 108,147 instances of handwritten words, distributed over 13,867 lines and 23,115 unique words, this is currently the 'largest and most comprehensive dataset' in this field. We also provided the bounding box annotations (YOLO format) for the segmentation of words/lines and the ground truth annotations for full-text, along with the segmented images and their positions. The contents of our dataset came from a diverse news category, and annotators of different ages, genders, and backgrounds, having variability in writing styles. The BN-HTRd dataset can be adopted as a basis for various handwriting classification tasks such as end-to-end document recognition, word-spotting, word/line segmentation, and so on. 

The statistics of the original dataset are given below:

Number of writers = 150\
Total number of images = 786\
Total number of lines = 14,383\
Total number of words = 1,08,181\
Total number of unique words = 23,115\
Total number of punctuation = 7,446\
Total number of characters = 5,74,203\ ### Steps to reproduce
See the Paper: URL

 #### Paper Information for Citation
TAGS
#task_categories-image-segmentation #task_categories-image-to-text #size_categories-10K<n<100K #language-Bengali #license-cc-by-4.0 #Handwriting Recognition #Document Imaging #Annotation #Image Segmentation #Bengali Language #Word Spotting #arxiv-2206.08977 #doi-10.57967/hf/0546 #region-us 
 # * BN-HTRd Splitted Dataset for Experimentation * # <u>Original Dataset:</u> "BN-HTRd: A Benchmark Dataset for Document Level Offline Bangla Handwritten Text Recognition (HTR)"
Link: URL ### Description
We introduce a new dataset for offline Handwritten Text Recognition (HTR) from images of Bangla scripts comprising words, lines, and document-level annotations. The BN-HTRd dataset is based on the BBC Bangla News corpus - which acted as ground truth texts for the handwritings. Our dataset contains a total of 786 full-page images collected from 150 different writers. With a staggering 108,147 instances of handwritten words, distributed over 13,867 lines and 23,115 unique words, this is currently the 'largest and most comprehensive dataset' in this field. We also provided the bounding box annotations (YOLO format) for the segmentation of words/lines and the ground truth annotations for full-text, along with the segmented images and their positions. The contents of our dataset came from a diverse news category, and annotators of different ages, genders, and backgrounds, having variability in writing styles. The BN-HTRd dataset can be adopted as a basis for various handwriting classification tasks such as end-to-end document recognition, word-spotting, word/line segmentation, and so on. 

The statistics of the original dataset are given below:

Number of writers = 150\
Total number of images = 786\
Total number of lines = 14,383\
Total number of words = 1,08,181\
Total number of unique words = 23,115\
Total number of punctuation = 7,446\
Total number of characters = 5,74,203\ ### Steps to reproduce
See the Paper: URL

 #### Paper Information for Citation
passage: TAGS
#task_categories-image-segmentation #task_categories-image-to-text #size_categories-10K<n<100K #language-Bengali #license-cc-by-4.0 #Handwriting Recognition #Document Imaging #Annotation #Image Segmentation #Bengali Language #Word Spotting #arxiv-2206.08977 #doi-10.57967/hf/0546 #region-us 
# * BN-HTRd Splitted Dataset for Experimentation *# <u>Original Dataset:</u> "BN-HTRd: A Benchmark Dataset for Document Level Offline Bangla Handwritten Text Recognition (HTR)"
Link: URL