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.