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descriptron

Image annotation, phenomics and evidence-tiered species descriptions.

pip install torch==2.10.0 torchvision==0.25.0 --index-url https://download.pytorch.org/whl/cu128   # NVIDIA; Mac/CPU: drop --index-url
SAM2_BUILD_CUDA=0 pip install git+https://github.com/facebookresearch/sam2.git   # SAM2 library (Windows: set SAM2_BUILD_CUDA=0 first)
pip install descriptron          # analysis programs, detectors and the GUI
descriptron-gui                  # first start downloads the SAM2 model file (898 MB) once
descriptron --list               # the 62 analysis programs

SAM2 is not on PyPI, so it cannot be installed with this package: install it from Meta's GitHub as above, into the same Python (3.10 or newer; 3.12 recommended). The GUI downloads the SAM2 model file sam2_hiera_large.pt once into ~/.cache/descriptron/sam2/; if you already have it, copy it there or set DESCRIPTRON_SAM2_CHECKPOINT. Step by step for Windows, macOS and Linux: https://github.com/alexrvandam/Descriptron/blob/main/docs/INSTALL_PIP.md

This is a convenience package with no code of its own. It installs:

descriptron-core the analysis half — pure pip, no torch, no GPU, no compiler
descriptron-vision torchvision detectors, SAM2-PAL propagation, DINOv3 landmark transfer
descriptron-gui the annotation GUI

If you only want to reproduce an analysis from deposited COCO files, install descriptron-core alone: it needs no model of any kind and installs in about a minute on Linux, macOS and Windows.

Detectron2 is an optional advanced backend and is not installed here — it has no PyPI wheel and needs a compiler. See the repository for the Docker image that carries it ready to run.

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