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# dhSegment | ||
# dhSegment text | ||
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[![Documentation Status](https://readthedocs.org/projects/dhsegment/badge/?version=latest)](https://dhsegment.readthedocs.io/en/latest/?badge=latest) | ||
This a fork of the original [dhSegment repository](https://github.com/dhlab-epfl/dhSegment). It contains the code used for the experiments of the paper: | ||
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**dhSegment** is a tool for Historical Document Processing. Its generic approach allows to segment regions and | ||
extract content from different type of documents. See | ||
[some examples here](https://dhsegment.readthedocs.io/en/latest/intro.html#use-cases). | ||
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The complete description of the system can be found in the corresponding [paper](https://arxiv.org/abs/1804.10371). | ||
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It was created by [Benoit Seguin](https://twitter.com/Seguin_Be) and Sofia Ares Oliveira at DHLAB, EPFL. | ||
``` | ||
Barman, Raphaël, Ehrmann, Maud, Clematide, Simon, Ares Oliveira, Sofia, and Kaplan, Frédéric (2020). | ||
Combining Visual and Textual Features for Semantic Segmentation of Historical Newspapers. | ||
Journal of Data Mining and Digital Humanities. https://arxiv.org/abs/2002.06144 | ||
``` | ||
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## Installation and usage | ||
The [installation procedure](https://dhsegment.readthedocs.io/en/latest/start/install.html) | ||
and examples of usage can be found in the documentation (see section below). | ||
## Modifications | ||
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## Demo | ||
Have a try at the [demo](https://dhsegment.readthedocs.io/en/latest/start/demo.html) to train (optional) and apply dhSegment in page extraction using the `demo.py` script. | ||
The following modifications were made: | ||
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## Documentation | ||
- Changing the input pipeline to read embeddings | ||
- Creation of embeddings maps with several dimensionality reduction algorithms | ||
- Concatenation of the embeddings map inside the encoder or decoder | ||
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*Under construction* | ||
## Usage | ||
For general usage of dhSegment, see the [original documentation](https://dhsegment.readthedocs.io/). | ||
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The documentation is available on [readthedocs](https://dhsegment.readthedocs.io/). | ||
- The csv file now needs four columns: image, label, embeddings, embeddings_map. | ||
- Different configuration options were added for choosing the different hyperparamters and can be found in `dh_segment_text/utils/params_config.py` and in the encoder and decoder. | ||
- An example config can be found under `embeddings_config.json`. | ||
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## | ||
If you are using this code for your research, you can cite the corresponding paper as : | ||
``` | ||
@inproceedings{oliveiraseguinkaplan2018dhsegment, | ||
title={dhSegment: A generic deep-learning approach for document segmentation}, | ||
author={Ares Oliveira, Sofia and Seguin, Benoit and Kaplan, Frederic}, | ||
booktitle={Frontiers in Handwriting Recognition (ICFHR), 2018 16th International Conference on}, | ||
pages={7--12}, | ||
year={2018}, | ||
organization={IEEE} | ||
} | ||
``` | ||
The training can be launched using the trainer script with `python dh_segment_train.py with /path/to/config.json`. |