diff --git a/.github/workflows/dependency-review.yml b/.github/workflows/dependency-review.yml new file mode 100644 index 0000000..b0dedc4 --- /dev/null +++ b/.github/workflows/dependency-review.yml @@ -0,0 +1,20 @@ +# Dependency Review Action +# +# This Action will scan dependency manifest files that change as part of a Pull Request, surfacing known-vulnerable versions of the packages declared or updated in the PR. Once installed, if the workflow run is marked as required, PRs introducing known-vulnerable packages will be blocked from merging. +# +# Source repository: https://github.com/actions/dependency-review-action +# Public documentation: https://docs.github.com/en/code-security/supply-chain-security/understanding-your-software-supply-chain/about-dependency-review#dependency-review-enforcement +name: 'Dependency Review' +on: [pull_request] + +permissions: + contents: read + +jobs: + dependency-review: + runs-on: ubuntu-latest + steps: + - name: 'Checkout Repository' + uses: actions/checkout@v3 + - name: 'Dependency Review' + uses: actions/dependency-review-action@v3 diff --git a/.github/workflows/label.yml b/.github/workflows/label.yml deleted file mode 100644 index 4613569..0000000 --- a/.github/workflows/label.yml +++ /dev/null @@ -1,22 +0,0 @@ -# This workflow will triage pull requests and apply a label based on the -# paths that are modified in the pull request. -# -# To use this workflow, you will need to set up a .github/labeler.yml -# file with configuration. For more information, see: -# https://github.com/actions/labeler - -name: Labeler -on: [pull_request_target] - -jobs: - label: - - runs-on: ubuntu-latest - permissions: - contents: read - pull-requests: write - - steps: - - uses: actions/labeler@v4 - with: - repo-token: "${{ secrets.GITHUB_TOKEN }}" diff --git a/.github/workflows/python-app.yml b/.github/workflows/python-app.yml new file mode 100644 index 0000000..130de9b --- /dev/null +++ b/.github/workflows/python-app.yml @@ -0,0 +1,41 @@ +# This workflow will install Python dependencies, run tests and lint with a single version of Python +# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python + +name: Python application + +on: + push: + branches: [ "main" ] + pull_request: + branches: [ "main" ] + +permissions: + contents: read + +jobs: + build: + + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v3 + - name: Set up Python 3.10 + uses: actions/setup-python@v3 + with: + python-version: "3.10" + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install flake8 pytest + if [ -f requirements.txt ]; then + grep -v 'gpu-control' requirements.txt | xargs pip install + fi + - name: Lint with flake8 + run: | + # stop the build if there are Python syntax errors or undefined names + flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics + # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide + flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics + - name: Main code Updated + run: | + python Check_MCUS.py diff --git a/README.md b/README.md index e513a7d..b84e039 100644 --- a/README.md +++ b/README.md @@ -1,10 +1,15 @@ # Pneumonia Detection AI +[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) +[![CodeQL](https://github.com/Aydinhamedi/Pneumonia-Detection-Ai/actions/workflows/codeql.yml/badge.svg?branch=main)](https://github.com/Aydinhamedi/Pneumonia-Detection-Ai/actions/workflows/codeql.yml) +[![Dependency Review](https://github.com/Aydinhamedi/Pneumonia-Detection-Ai/actions/workflows/dependency-review.yml/badge.svg)](https://github.com/Aydinhamedi/Pneumonia-Detection-Ai/actions/workflows/dependency-review.yml)\ +[![Python application](https://github.com/Aydinhamedi/Pneumonia-Detection-Ai/actions/workflows/python-app.yml/badge.svg)](https://github.com/Aydinhamedi/Pneumonia-Detection-Ai/actions/workflows/python-app.yml) ### This project uses a deep learning model built with the TensorFlow framework to detect pneumonia in X-ray images. The model architecture is based on the EfficientNetB7 model, which has achieved an accuracy of approximately 97.12% (97.11538%) on our test data. This high accuracy rate is one of the strengths of our AI model. > [!IMPORTANT] > The code that have achived the highest acc is `backup/V6/Model_T&T.ipynb`.\ > And the code with the light model is `backup/V7/Model_T&T.ipynb`. + ## Usage > [!TIP] > If you just want the model go to the Github Releases.