tree-disk-pith

Tree Disk Pith Detection

A Python package for analyzing tree rings in cross-sectional images. Originally forked from hmarichal93/apd.

Installation

pip install tree-disk-pith

Usage

Python API

import treediskpith

# Configure the analyzer
treediskpith.configure(
    input_image="input/tree-disk4.png",
    model_path="models/apd_dl.h5",
    save_results=True,
)

# Run the detection
(
    img_in,          # Original input image
    img_pre,         # Preprocessed image
    pith,  # Center of the tree disk
) = treediskpith.run()

Command Line Interface (CLI)

Basic usage:

tree-disk-pith --input_image ./input/tree-disk4-seg.jpg --model_path ./models/yolo11s-det-pith.pt

Advanced usage with custom parameters:

tree-disk-pith \
    --input_image input/tree-disk3.png \
    --model_path ./models/yolo11s-det-pith.pt \
    --output_dir custom_output/ \
    --new_shape 640 \
    --save_results \
    --debug

CLI Arguments

Argument	Type	Required	Default	Description
--input_image	str	Yes	-	Input image file path
--output_dir	str	Yes	./output	Output directory path
--model_path	str	No	-	Path to the weights file (required if using apd_dl method)
--new_shape	int	No	0	New shape for resizing the input image. If 0, no resizing is done
--debug	flag	No	False	Enable debug mode to save intermediate images and outputs
--save_results	flag	No	False	Save intermediate images, labelme and config file

Development

Setting up Development Environment

1. Create and activate virtual environment:

poetry config virtualenvs.in-project true
poetry env use python

poetry install
eval $(poetry env activate)

1. Running tests:

pytest

1. fetch dataset

python fetch_dataset.py

1. Download pretrained model

python fetch_pretrained_model.py