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https://github.com/scanner-research/scanner
Efficient video analysis at scale
https://github.com/scanner-research/scanner
big-data cpp distributed gpu python video
Last synced: about 12 hours ago
JSON representation
Efficient video analysis at scale
- Host: GitHub
- URL: https://github.com/scanner-research/scanner
- Owner: scanner-research
- License: apache-2.0
- Created: 2016-07-06T22:07:28.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2023-06-01T18:10:56.000Z (over 1 year ago)
- Last Synced: 2024-04-14T06:11:04.758Z (10 months ago)
- Topics: big-data, cpp, distributed, gpu, python, video
- Language: C++
- Homepage: https://scanner-research.github.io/
- Size: 68 MB
- Stars: 613
- Watchers: 52
- Forks: 108
- Open Issues: 81
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Scanner: Efficient Video Analysis at Scale [](https://GitHub.com/scanner-research/scanner/tags/) [](https://travis-ci.org/scanner-research/scanner) #
Scanner is a system for developing applications that efficiently process large video datasets.
To learn more about Scanner, see the documentation at [scanner.run](http://scanner.run), check out the [various example applications](https://github.com/scanner-research/scanner/tree/master/examples), or read the SIGGRAPH 2018 Technical Paper: "[Scanner: Efficient Video Analysis at Scale](http://graphics.stanford.edu/papers/scanner/)".
## Documentation
Scanner's documentation is hosted at [scanner.run](http://scanner.run). Here
are a few links to get you started:
* [Installation](http://scanner.run/installation.html)
* [Getting Started](http://scanner.run/getting-started.html)
* [Programming Handbook](http://scanner.run/programming-handbook.html)
* [API Reference](http://scanner.run/api.html)
* [SIGGRAPH 2018 Technical Paper](http://graphics.stanford.edu/papers/scanner/scanner_sig18.pdf)
* [Scanner Examples](https://github.com/scanner-research/scanner/tree/master/examples)
## Contributing
If you'd like to contribute to the development of Scanner, you should first
build Scanner [from source](http://scanner.run/from_source.html).
Please submit a pull-request rebased against the most recent version of the
master branch and we will review your changes to be merged. Thanks for
contributing!
### Running tests
You can run the full suite of tests by executing `make test` in the directory
you used to build Scanner. This will run both the C++ tests and the end-to-end
tests that verify the python API.
## About
Scanner is an active research project, part of a collaboration between Stanford and Carnegie Mellon University. Please contact [Alex Poms](https://github.com/apoms) and [Will Crichton](https://github.com/willcrichton) with questions.
Scanner was developed with the support of the NSF (IIS-1539069), the Intel Corporation (through the Intel Science and Technology Center for Visual Cloud Computing and the NSF/Intel VEC program), and by Google.
### Paper citation
Scanner was published at SIGGRAPH 2018 as "[Scanner: Efficient Video Analysis at Scale](http://graphics.stanford.edu/papers/scanner/)" by Poms, Crichton, Hanrahan, and Fatahalian. If you use Scanner in your research, we'd appreciate it if you cite the paper with the following bibtex:
```
@article{Poms:2018:Scanner,
author = {Poms, Alex and Crichton, Will and Hanrahan, Pat and Fatahalian, Kayvon},
title = {Scanner: Efficient Video Analysis at Scale},
journal = {ACM Trans. Graph.},
issue_date = {August 2018},
volume = {37},
number = {4},
month = jul,
year = {2018},
issn = {0730-0301},
pages = {138:1--138:13},
articleno = {138},
numpages = {13},
url = {http://doi.acm.org/10.1145/3197517.3201394},
doi = {10.1145/3197517.3201394},
acmid = {3201394},
publisher = {ACM},
address = {New York, NY, USA},
}
```