diff --git a/README.md b/README.md index c556f332a45d95d29ca8f6ea601e3a7d90d64c8d..a6a6de7e5881aa54cf87d78277675170d9c7605d 100644 --- a/README.md +++ b/README.md @@ -7,43 +7,24 @@ MOD 4.6 Deep Learning & Artificial Intelligence The objective of this tutorial is to write a complete image classification program in Python. Two classification models will be successively developed and tested: k-nearest neighbors (KNN) and neural networks (NN). -## Add your files +## Requirements -- [ ] [Create](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#create-a-file) or [upload](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#upload-a-file) files -- [ ] [Add files using the command line](https://docs.gitlab.com/ee/gitlab-basics/add-file.html#add-a-file-using-the-command-line) or push an existing Git repository with the following command: +In this tutorial we use Python 3.7 or higher and the library numpy. -``` -cd existing_repo -git remote add origin https://gitlab.ec-lyon.fr/marab/image-classification.git -git branch -M main -git push -uf origin main -``` +## Usage -## Integrate with your tools +The image database used for the experiments is CIFAR-10 which consists of 60 000 color images of size 32x32 divided into 10 classes (plane, car, bird, cat, ...). +This database can be obtained at the address https://www.cs.toronto.edu/~kriz/cifar.html where are also given the indications to read the data. -- [ ] [Set up project integrations](https://gitlab.ec-lyon.fr/marab/image-classification/-/settings/integrations) -## Collaborate with your team +The python file named read_cifar.py contains the functions needed to read the data. -- [ ] [Invite team members and collaborators](https://docs.gitlab.com/ee/user/project/members/) -- [ ] [Create a new merge request](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html) -- [ ] [Automatically close issues from merge requests](https://docs.gitlab.com/ee/user/project/issues/managing_issues.html#closing-issues-automatically) -- [ ] [Enable merge request approvals](https://docs.gitlab.com/ee/user/project/merge_requests/approvals/) -- [ ] [Automatically merge when pipeline succeeds](https://docs.gitlab.com/ee/user/project/merge_requests/merge_when_pipeline_succeeds.html) +The python file named knn.py contains the functions developping and testing the k-nearest neighbors classification model. -## Test and Deploy - -Use the built-in continuous integration in GitLab. - -- [ ] [Get started with GitLab CI/CD](https://docs.gitlab.com/ee/ci/quick_start/index.html) -- [ ] [Analyze your code for known vulnerabilities with Static Application Security Testing(SAST)](https://docs.gitlab.com/ee/user/application_security/sast/) -- [ ] [Deploy to Kubernetes, Amazon EC2, or Amazon ECS using Auto Deploy](https://docs.gitlab.com/ee/topics/autodevops/requirements.html) -- [ ] [Use pull-based deployments for improved Kubernetes management](https://docs.gitlab.com/ee/user/clusters/agent/) -- [ ] [Set up protected environments](https://docs.gitlab.com/ee/ci/environments/protected_environments.html) +The python file named mlp.py contains the functions developping and testing the multilayer perceptron neural networks classification model. *** - ## Author Myla Arab