https://github.com/tpsatish95/indus-script-ocr
The Indus script optical grapheme recognition engine (from archaeological artifact images)
https://github.com/tpsatish95/indus-script-ocr
ancient-texts caffe computer-vision deep-learning digital-humanities epigraphy opencv optical-character-recognition pipeline scikit-image scikit-learn
Last synced: about 1 year ago
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The Indus script optical grapheme recognition engine (from archaeological artifact images)
- Host: GitHub
- URL: https://github.com/tpsatish95/indus-script-ocr
- Owner: tpsatish95
- License: apache-2.0
- Created: 2017-03-23T14:32:52.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2017-10-12T19:28:13.000Z (over 8 years ago)
- Last Synced: 2025-04-14T23:10:05.379Z (about 1 year ago)
- Topics: ancient-texts, caffe, computer-vision, deep-learning, digital-humanities, epigraphy, opencv, optical-character-recognition, pipeline, scikit-image, scikit-learn
- Language: Python
- Size: 30.3 KB
- Stars: 17
- Watchers: 2
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Indus Script OCR
To automatically locate text patches/regions, segment individual symbols/characters from those regions and also identify each symbol/character belonging to the Indus Script, given images of Indus seals from archaeological sites, using image processing and deep learning techniques. [WIP]
View our research article titled "__Deep Learning the Indus Script__" arXived at: [arXiv:1702.00523v1](https://arxiv.org/abs/1702.00523v1)
## Deploying the app
- Setup the GPU machine to run the service,
- Install latest nvidia drivers, from `http://www.geforce.com/drivers`
- Install the nvidia-docker plug-in over docker, from `https://github.com/NVIDIA/nvidia-docker/releases`
- Make sure you have `git-lfs` installed (https://git-lfs.github.com/)
- Launch the service,
- Build the docker image: `nvidia-docker build --no-cache=true -t indus-script-ocr:latest .`
- To launch a docker container: `nvidia-docker run -it -v "$PWD":/root/workspace --rm --env-file app.env --name indus-script-ocr-service indus-script-ocr:latest`
## Press Coverage:
- [The Verge](http://www.theverge.com/2017/1/25/14371450/indus-valley-civilization-ancient-seals-symbols-language-algorithms-ai#EQQA6r)
- [The Hindu](http://www.thehindu.com/sci-tech/science/chennai-team-taps-ai-to-read-indus-script/article17448690.ece)
- [Times of India](http://timesofindia.indiatimes.com/city/chennai/app-may-help-decipher-indus-valley-symbols/articleshow/57281369.cms)
- [SBS Radio, Australia](http://www.sbs.com.au/yourlanguage/tamil/en/content/app-decipher-ancient-symbols?language=en)
## Talks
- **Indian Deep Learning Initiative (IDLI):** [slide deck](https://github.com/tpsatish95/talks/blob/master/Deep\%20learning\%20based\%20OCR\%20engine\%20for\%20the\%20Indus\%20script\%20-\%20IDLI\%20Talk.pdf), [video](https://www.youtube.com/watch?v=qPF1oR9yMNY}), [link](https://www.facebook.com/groups/idliai/)
- **ThoughtWorks Geek Night:** [slide deck](https://github.com/tpsatish95/talks/blob/master/Deep\%20learning\%20based\%20OCR\%20engine\%20for\%20the\%20Indus\%20script\%20-\%20TW\%20Geek\%20Night.pdf), [video](https://www.youtube.com/watch?v=g7v4QaCD-UQ), [link](https://twchennai.github.io/geeknight/edition-43.html)
- **ChennaiPy:** [link](http://chennaipy.org/may-2017-meet-minutes.html)
- **Anthill Inside 2017:** [proposal](https://anthillinside.talkfunnel.com/2017/15-deep-learning-based-ocr-engine-for-the-indus-scrip)
## Citation
Please cite `indus-script-ocr` in your publications if it helps your research:
@article{palaniappan2017deep,
title={Deep Learning the Indus Script},
author={Palaniappan, Satish and Adhikari, Ronojoy},
journal={arXiv preprint arXiv:1702.00523},
year={2017}
}