How to design, implement, test, and deploy image classifiers, with deep neural networks.

This is project based learning, not research

Current version 0.1 (20220707)

1. Go to your home directory, make Apps directory, change directory

   $ cd ~; mkdir Apps && cd Apps

• Clone this repo

  $ git clone [email protected]:daniel_walther_berns/how_to_image_classifier.git

• Change directory

  $ cd how_to_image_classifier/

• Run start.sh

  $ ./start.sh

The bash script start.sh

1. creates a python3 environment ditdic (design, implement, test and deploy image classifiers);
2. installs some dependences;
3. installs the ditdic package;
4. creates directory ~/Data/how_to_image_classifier/v_0_1

Created directories

~/Apps/how_to_image_classifier

~/.venvs/ditdic

~/Data/how_to_image_classifier/v_0_1

In the ~/Apps/how_to_image_classifier/docs directory,

$ cd ~/Apps/how_to_image_classifier/docs

you will find documents related to data, software, hardware, installation, and operations of this project.

In the ~/Apps/how_to_image_classifier/source directory,

$ cd ~/Apps/how_to_image_classifier/source

you will find a set of jupyter notebooks, the package ditdic and a README.md.

You can use the notebooks and the package ditdic following the next instructions:

0. Make sure you have executed ~/Apps/how_to_image_classifier/start.sh
1. Activate the environment $ . ~/.venvs/ditdic/bin/activate
2. Change directory $ cd notebooks/
3. Run jupyter $ jupyter notebook

Write

• Repo owner: Daniel Walther Berns
• twitter: @daniel_berns
• github: https://github.com/DanielBerns