Compilation of Dockerfiles with automated builds enabled on the Docker Hub. Not suitable for production environments. These images are under continuous development, so breaking changes may be introduced.
Nearly all images are based on Ubuntu Core 14.04 LTS, built with minimising size/layers and best practices in mind.
Some builds based on certain software have builds that are triggered on schedule via a cron script to stay up to date on a weekly basis. These are:
Most containers run as a foreground process. To daemonise (in Docker terminology, detach) such a container it is possible to use:
docker run -d <image> sh -c "while true; do :; done"
It is now possible to access the daemonised container, for example using bash:
docker exec -it <id> bash
Caffe is a deep learning framework made with expression, speed, and modularity in mind.
It is developed by the Berkeley Vision and Learning Center (BVLC) and community contributors.
This Docker image Caffe is compiled with OpenCV3 and Anaconda support
The demo server requires Python with some dependencies. To make sure you have the dependencies, please run
pip install -r examples/web_demo/requirements.txt
and also make sure that you’ve compiled the Python Caffe interface and that it is on your PYTHONPATH
Use Caffe Web Demo Docker:
docker pull flyingmouse/caffe-ocr docker run -p 80:5000 -d flyingmouse/caffe-ocr
Automated Builds on the Docker Hub have several advantages, including reproducibility and security. However the build cluster has the following limits for Automated Builds:
- 2 hours
- 1 CPU
- 2 GB RAM
- 512 MB swap
- 30 GB disk space
The main tip for keeping within the CPU and memory limits is to reduce parallelism/forking processes. Due to their logging system, redirecting stdout/stderr to /dev/null can potentially save a reasonable amount of memory.