sleap-roots

Analysis tools for SLEAP-based plant root phenotyping.

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📦 Installation

For End Users

pip install sleap-roots

For Development (Recommended: uv)

uv is a fast Python package manager (10-100x faster than conda):

# Install uv (one-time setup)
curl -LsSf https://astral.sh/uv/install.sh | sh

# Clone and setup
git clone https://github.com/talmolab/sleap-roots && cd sleap-roots
uv sync

# Run commands
uv run pytest tests/
uv run black sleap_roots tests

Why uv? Environment setup in ~30 seconds (vs 10-15 minutes with conda) with reproducible builds via lockfile.

Alternative: conda

conda env create -f environment.yml
conda activate sleap-roots

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🌱 Usage

Trait pipelines supported:

• DicotPipeline – Primary + lateral roots (e.g. soy, canola)
• YoungerMonocotPipeline – Primary + crown roots (e.g. early rice)
• OlderMonocotPipeline – Crown roots only (e.g. later rice)
• PrimaryRootPipeline – Primary root only
• LateralRootPipeline – Lateral roots only
• MultipleDicotPipeline – Multi-plant dicot setup (batch from a single image)

🔁 Example: Dicot Pipeline

1. Compute traits for a single plant

import sleap_roots as sr

series = sr.Series.load(
    series_name="919QDUH",
    h5_path="tests/data/canola_7do/919QDUH.h5",
    primary_path="tests/data/canola_7do/919QDUH.primary.slp",
    lateral_path="tests/data/canola_7do/919QDUH.lateral.slp"
)

pipeline = sr.DicotPipeline()
traits = pipeline.compute_plant_traits(series, write_csv=True)

2. Compute traits for a batch

paths = sr.find_all_slp_paths("tests/data/soy_6do")
plants = sr.load_series_from_slps(paths, h5s=True)

pipeline = sr.DicotPipeline()
batch_df = pipeline.compute_batch_traits(plants, write_csv=True)

3. Use a single trait utility

from sleap_roots.lengths import get_root_lengths

pts = series.get_primary_points(frame_idx=0)
lengths = get_root_lengths(pts)

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📓 Notebooks & Tutorials

Explore tutorials under notebooks/:

cd notebooks
jupyter lab

You can use the test data in tests/data or replace it with your own.

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🧪 Development

Using uv (Recommended)

# 1. Clone the repository
git clone https://github.com/talmolab/sleap-roots && cd sleap-roots

# 2. Install dependencies (creates .venv automatically)
uv sync

# 3. Run tests
uv run pytest tests/

# 4. Format code
uv run black sleap_roots tests

# 5. Check docstrings
uv run pydocstyle sleap_roots/

Adding dependencies:

uv add numpy  # Add runtime dependency
uv add --group dev pytest  # Add dev dependency

Using conda (Alternative)

# 1. Clone the repository
git clone https://github.com/talmolab/sleap-roots && cd sleap-roots

# 2. Create environment
conda env create -f environment.yml
conda activate sleap-roots

# 3. Run tests
pytest tests/

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📖 Trait Reference

See the latest trait documentation here:

👉 HackMD: sleap-roots Trait Docs

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🤝 Acknowledgments

Created by the Talmo Lab and Busch Lab at the Salk Institute, as part of the Harnessing Plants Initiative.

Contributors

• Elizabeth Berrigan
• Lin Wang
• Andrew O'Connor
• Talmo Pereira

Citation

E.M. Berrigan et al., "Fast and Efficient Root Phenotyping via Pose Estimation", Plant Phenomics.
DOI: 10.34133/plantphenomics.0175