Tools

Software

IFML maintains research-oriented software tools that support digitization, visualization, and analysis workflows. Tools are tracked in a structured registry that records development status, scope, and dependencies. Status labels (Alpha / Beta) indicate intended use and validation scope, not a guarantee of fitness for any particular purpose.

DART — Dendro Analysis & Reporting Tool

Beta

A specialized desktop workbench for the manual annotation and quantitative analysis of high-resolution tree-ring imagery.

Designed to replace traditional manual measuring with a caliper, DART provides a precise digital environment for “on-screen” dendrochronology, handling multi-gigabyte archival scans that typically overwhelm standard image viewers. Sub-pixel calibration, vector annotation, and standard RWL/CSV exports for downstream crossdating and chronology toolchains.

Stack Electron Node.js Sharp / libvips OpenSeadragon Fabric.js
View Technical Overview RepositoryWIP

DART: ChipLab

Beta

A desktop application that detects, measures, and species-classifies woodchips from flatbed scanner images — fully offline.

A companion to DART for wood-products research and mill QA. ChipLab converts a single flatbed scan into per-chip geometry (length, width, area, aspect ratio) and per-chip species predictions with confidence scores, using Mask R-CNN segmentation with SAM2 human-in-the-loop correction. Runs entirely offline; no data leaves the machine.

Stack Electron Python Mask R-CNN (MMDetection) SAM2 EfficientNet / ResNet-50
View Technical Overview RepositoryWIP

IFML Archive Manager

Alpha

A custom Python-based toolkit designed to streamline the digitization workflow.

Automates the ingestion of high-resolution TIFF scans, preserves documented color and metadata attributes, and generates web-accessible Access Packages for deposit on Zenodo.

Stack Python 3 OpenCV Pillow (PIL) Zenodo API

Software Validity & Reproducibility

Guidance for Use

  • Validity: IFML software is provided as-is for research support. Outputs may contain errors and should be independently validated prior to publication or decision-critical use.
  • Reproducibility: Outputs may vary across operating systems, dependency versions, calibration choices, and model weights. Document software versions and dataset identifiers in any derived work.
  • System Requirements: Standard desktop environment (Windows 10+ / macOS 12+), 8 GB+ RAM, SSD storage recommended.