qc-studio

Prototyping repo for creating visual QC workflow that can be integrated with Nipoppy. See design overview here.

Goals

• Create a web-app to visualize pipeline output including reports, svg / png images, and 3D MRI files
• Pre-define a set of files in a <pipeline-name>_qc.json config file that will be visualized in the web-app

Installation

These instructions show how to create a Python virtual environment and install the project's runtime dependencies.

Prerequisites

• Python 3.10+ (3.12 tested in CI/DEV environment)

Create and activate a virtual environment

# from the project root
python3 -m venv .venv
source .venv/bin/activate

# upgrade packaging tools (recommended)
python -m pip install --upgrade pip setuptools wheel

Install dependencies

python -m pip install -r requirements.txt

Install niivue-streamlit component

pip install --index-url https://test.pypi.org/simple/ --no-deps niivue-streamlit

Run example workflow (uses files from sample_data)

cd ui
./fmriprep_test.sh