85 lines
2.4 KiB
Markdown
85 lines
2.4 KiB
Markdown
# FU Berlin - Image Processing SS 18
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The assignments will be published to this repository.
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All assignments will be IPython Notebooks. That you have to complete.
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## Work flow
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The rough workflow is:
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1. You clone this repository.
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2. Edit the exercises.
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3. Push it to your private repository.
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4. I fetch your code when the assignment is due. (Every Wednesday at 8:00 a.m.)
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5. You fetch the latest assignments from this repository.
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It is required to use private git repositories.
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The university offers free private repositories [here](https://git.imp.fu-berlin.de/)
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or you can get [5 GitHub repositories for free](https://education.github.com/) as a student.
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First clone this repository:
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```
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$ git clone --origin upstream https://github.com/BildverarbeitungSS18/Hausaufgaben
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```
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Get into the new folder
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```
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$ cd Hausaufgaben
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```
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Add your remote
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```
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$ git remote add origin <your git repo url>
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```
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Please clear the notebook's output before committing. Otherwise the repository
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size can get pretty big.
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The best thing is to setup a `pre-commit` hook that removes the outputs before
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the files are committed:
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```
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$ ln -s ../../nb_strip_output.py .git/hooks/pre-commit
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```
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Otherwise you manually clean the output with `Cell -> All Output -> Clear` or
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use the `nb_strip_output.py <filename>` script.
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To get the latest assignments into your repository see [how to sync a fork](https://help.github.com/articles/syncing-a-fork/).
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Paste a link to your repository into the kvv assignment box.
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Make sure that I have read and write rights on your repository.
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Please give us read access to your repository. Add 'garlicpasta' and 'BildverarbeitungSS18' on github
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or 'jakobkrause' as well as 'nbobenko' on fu gitlab.
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## Docker
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There exists a script for a [docker](https://www.docker.com/) image.
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All the libraries we will use are included in this image.
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It is recommended to use the image, but you are free to setup the environment
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for yourself.
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First [install docker](https://docs.docker.com/engine/installation/) on your computer.
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Build the image:
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```
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$ ./docker_build.sh
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```
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The build script will create a user with your username and uid inside the image.
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It may take some minutes until the image is built.
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If you don't have a bash you can manually edit the `Dockerfile.sample`.
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See the docker documentation for [details](https://docs.docker.com/)
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To run the image:
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```
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$ ./docker_start.sh
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```
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Now visit [localhost:8888](http://localhost:8888). Jupyter Notebook
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should be ready to use.
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