environment.yml

# GAZE2CodeToolkit — Conda environment specification.
#
# This file installs the scientific stack via conda-forge (faster, fewer
# build issues than pip on Windows/macOS) and pins everything else through
# `pip install -r requirements.txt`.
#
# Tesseract OCR binary is included via conda-forge so users do not need a
# separate system install.
#
# Usage:
#     conda env create -f environment.yml
#     conda activate gaze2code
#     # Verify:
#     python -c "from g2c.parsers import available_datasets; print(available_datasets())"

name: gaze2code

channels:
  - conda-forge

dependencies:
  - python=3.10
  # Scientific core — conda-forge builds work cross-platform out of the box.
  - numpy>=1.23
  - pandas>=2.0
  - scipy>=1.10
  - matplotlib>=3.7
  - seaborn>=0.13
  - opencv>=4.8           # conda-forge `opencv` ≡ pip `opencv-python`
  - pillow>=10.0
  - tqdm>=4.66
  # Expertise-classification stack (used by g2c/classification and cli/classify_expertise).
  - scikit-learn>=1.3
  - xgboost>=2.0
  # OCR binary — bundled here so users do not install via apt/brew separately.
  - tesseract>=5.3
  - pip
  - pip:
      # Everything else flows through pip + requirements.txt.
      - -r requirements.txt