https://github.com/oneoffcoder/docker-containers
A collection of pedantic docker containers.
https://github.com/oneoffcoder/docker-containers
deep-learning docker-containers docker-images jupyter nlp object-detection python raspberry-pi yolo
Last synced: 4 months ago
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A collection of pedantic docker containers.
- Host: GitHub
- URL: https://github.com/oneoffcoder/docker-containers
- Owner: oneoffcoder
- Created: 2019-07-18T22:36:22.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2023-05-11T01:10:09.000Z (over 2 years ago)
- Last Synced: 2025-04-06T03:33:37.649Z (10 months ago)
- Topics: deep-learning, docker-containers, docker-images, jupyter, nlp, object-detection, python, raspberry-pi, yolo
- Language: Python
- Homepage:
- Size: 53.6 MB
- Stars: 30
- Watchers: 2
- Forks: 7
- Open Issues: 28
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
Awesome Lists containing this project
README
# Intro
These are some sample docker containers for learning purposes.
# x86 Docker Images
* [dl-classifier](dl-classifier): An executable [container](https://hub.docker.com/r/oneoffcoder/dl-classifier) with [all of PyTorch's convolutional neural networks](https://pytorch.org/docs/stable/torchvision/models.html) (CNNs).
* [dl-darknet](dl-darknet): [YOLO object detection](https://github.com/pjreddie/darknet) with [darknet](https://github.com/AlexeyAB/darknet) in a [box](https://hub.docker.com/r/oneoffcoder/dl-darknet)!
* [dl-pose-yolo](dl-pose-yolo): A modified [YOLO v3 Pytorch](https://github.com/eriklindernoren/PyTorch-YOLOv3) implementation used for detecting humans for pose estimation.
* [dl-pose-hrn](dl-pose-hrn): A modified [Deep High-Resolution Network](https://github.com/leoxiaobin/deep-high-resolution-net.pytorch) implementation used for pose estimation.
* [dl-transfer](dl-transfer): An executable neural style transfer Docker image.
* [conda-deeplearning](conda-deeplearning): A [container](https://hub.docker.com/r/oneoffcoder/conda-deeplearning) with conda environment + Jupyter for Deep Learning.
* [conda-nlp](conda-nlp): A [container](https://hub.docker.com/r/oneoffcoder/conda-nlp) with conda environment + Jupyter for Natural Language Processing (NLP).
* [nginx-env](nginx-env): A [container](https://hub.docker.com/r/oneoffcoder/nginx-env) showing how to acquire environment variables at runtime for application configuration (externalizing properties).
* [nginx-port](nginx-port): A [container](https://hub.docker.com/r/oneoffcoder/nginx-port) showing how to run nginx on a port specified at runtime through an environment variable.
* [nginx-wsgi](nginx-wsgi): A [container](https://hub.docker.com/r/oneoffcoder/nginx-wsgi) showing how to run flask behind gunicorn and nginx.
* [nginx-stream-binary](nginx-stream-binary): A [container](https://hub.docker.com/r/oneoffcoder/nginx-stream-binary) showing how to stream back binary files (e.g. Word, Excel, PowerPoint and PDF).
* [docker-exe](docker-exe): A [project](https://hub.docker.com/r/oneoffcoder/docker-exe) showing how to build a container that may be used as an executable.
* [spark-jupyter](spark-jupyter): A [project](https://hub.docker.com/r/oneoffcoder/spark-jupyter) with Hadoop, Spark and Python that may be used to learn massively parallel processing.
* [java-jupyter](java-jupyter): A [project](https://hub.docker.com/r/oneoffcoder/java-jupyter) to learn Java 12.
* [cpp-cicd](cpp-cicd): A [C++](https://hub.docker.com/r/oneoffcoder/cpp-cicd) Docker image for building C++ projects using CMake and BOOST.
## Raspberry Pi Docker Images
* [rpi-python37](rpi-python37): A [container](https://hub.docker.com/r/oneoffcoder/rpi-python37) with Python 3.7 for use with Raspberry Pi 4.
* [rpi-base](rpi-base): A [container](https://hub.docker.com/r/oneoffcoder/rpi-base) for use with Raspberry Pi 4.
* [rpi-miniconda](rpi-miniconda): A [container](https://hub.docker.com/r/oneoffcoder/rpi-miniconda) with Miniconda and Python 3.6 for use with Raspberry Pi 4.
* [rpi-jupyterlab](rpi-jupyterlab): A [container](https://hub.docker.com/r/oneoffcoder/rpi-jupyterlab) with Python 3.6 + Jupyter Lab (and Notebook) for Raspberry Pi 4.
* [rpi-scikit](rpi-scikit): A [container](https://hub.docker.com/r/oneoffcoder/rpi-scikit) with Python 3.6 + Scikit-Learn + Jupyter Lab for Raspberry Pi 4.
* [rpi-nlp](rpi-nlp): A [container](https://hub.docker.com/r/oneoffcoder/rpi-nlp) with Python 3.6 + NLTK + gensim + Stanford Core NLP + textblob + Jupyter Lab for Raspberry Pi 4.
* [rpi-deeplearning](rpi-deeplearning): A [container](https://hub.docker.com/r/oneoffcoder/rpi-deeplearning) with Python 3.6 + Scikit-Learn + NLP + Tensorflow + Jupyter Lab for Raspberry Pi 4.
* [rpi-darknet](rpi-darkent): [YOLO object detection](https://github.com/pjreddie/darknet) with [darknet](https://github.com/AlexeyAB/darknet) in a [box](https://hub.docker.com/r/oneoffcoder/rpi-darknet) for Raspberry Pi 4! Be careful, not for the faint of heart!
## Raspberry Pi Images
Here are the dependencies between the RPi Docker images.
* rpi-base
* rpi-miniconda, rpi-darknet (from rpi-base)
* rpi-jupyterlab (from rpi-miniconda)
* rpi-scikit (from rpi-jupyterlab)
* rpi-nlp (from rpi-scikit)
* rpi-deeplearning (from rpi-nlp)
The rpi-python37 docker image does not depend on the others.
# Databricks Images
* [db-nlp](db-nlp): Customized Natural Language Processing (NLP) container for use with Databricks.
* [db-java](db-java): Template Docker container showing how to manage Java/Scala dependencies for use with Databricks.
# Docker Hub
All the images are published on [Docker Hub](https://hub.docker.com/u/oneoffcoder).
# Cleaning up
Remove all exited docker images
```bash
docker rm $(docker ps -q -f status=exited)
```
Remove all docker images that are dangling.
```bash
docker image rm $(docker images -f dangling=true -q)
```
Remove stopped container and images without any container associations.
```bash
docker system prune -a -f
```
# Citation
```
@misc{oneoffcoder_docker_containers_2019,
title={Docker Containers},
url={https://github.com/oneoffcoder/docker-containers},
journal={GitHub},
author={One-Off Coder},
year={2019},
month={Jul}}
```
# Copyright Stuff
```
Copyright 2019 One-Off Coder
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
```
# Contact
[One-Off Coder](https://cloud.docker.com/u/oneoffcoder/)
* [Website](https://www.oneoffcoder.com)
* [Twitter](https://twitter.com/oneoffcoder)
* [Facebook](https://www.facebook.com/oneoffcoder)
* [YouTube](https://www.youtube.com/channel/UCCCv8Glpb2dq2mhUj5mcHCQ)