A car recognizing and speed calculation platform.
CarCV consists of several modules:
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carcv-core — core detection and recognition module
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carcv-cpp — an old and deprecated implementation of this project in C++ with heavy use of OpenCV
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carcv-webapp — a Java EE web-app implementation of the CarCV Core
CarCV uses semantic versioning.
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See: How-to setup your build environment: Windows, Linux & Mac
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Recommended:
mvn clean install -DskipTests -
To run unit tests:
mvn clean install -
To run integration tests:
mvn clean install -Pit,wildfly -
To clean, run:
mvn clean -
Run a simple carcv-core demo
CarCV is also available as a Docker image:
sudo docker pull oskopek/carcv-webapp
sudo docker run -d --name=mariadb fedora/mariadb
sudo docker run -it --rm --link mariadb:mariadb -p 8080:8080 oskopek/carcv-webapp-
Post questions or comments on our Google Groups mailing list
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Join our IRC channel: Join #carcv on irc.freenode.net
Everyone is encouraged to help improve this project.
Here are some ways you can contribute:
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by using alpha, beta, and pre-release versions
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by reporting bugs
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by suggesting new features
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by implementing planned features
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by translating to a new language
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by writing specifications
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by writing code (no patch is too small: fix typos, add comments, clean up inconsistent whitespace)
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by refactoring code
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by closing issues
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by reviewing patches
We use the GitHub issue tracker to track bugs and features. Before submitting a bug report or feature request, check to make sure it hasn’t already been submitted. When submitting a bug report, please include a Gist that includes a stack trace and any details that may be necessary to reproduce the bug, including your Java version and operating system.
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Implement your feature or bug fix
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If applicable, add tests for your feature or bug fix
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Run
mvn clean install -Pit-
If you contributed to carcv-webapp, run:
mvn clean install -Pit,wildfly-it
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If the tests fail, return to step 3 and 4
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Add, commit, and push your changes