Correlation analysis between image properties and model predictions #202

	name: CI Pipeline

	on:
	push:
	branches: [ main, develop ]
	pull_request:
	branches: [ main, develop ]

	jobs:
	build-test:
	runs-on: ubuntu-latest
	timeout-minutes: 20
	strategy:
	matrix:
	python-version: ['3.11'] # Use a single version for deterministic Docker builds

	steps:
	- name: Checkout repository
	uses: actions/checkout@v4

	- name: Set up Python
	uses: actions/setup-python@v5
	with:
	python-version: ${{ matrix.python-version }}
	cache: 'pip'
	cache-dependency-path: requirements.txt

	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install torch==2.4.1+cpu torchvision==0.19.1+cpu --index-url https://download.pytorch.org/whl/cpu
	pip install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cpu
	pip install pytest pytest-cov flake8

	- name: Lint with Flake8
	run: \|
	flake8 src app tests --max-line-length=100

	- name: Run tests with coverage (host environment)
	run: \|
	pytest -q --disable-warnings --maxfail=1 \
	--cov=src --cov-report=term-missing --cov-fail-under=70

	- name: Build Docker image
	run: \|
	docker build -t pneumodetect:ci .

	- name: Run tests inside Docker
	run: \|
	docker run --rm pneumodetect:ci pytest -q --disable-warnings --maxfail=1 \
	--cov=src --cov-report=term-missing --cov-fail-under=70

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