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A package for tree disk pith detection in images

Project description

Tree Disk Pith Detection

PyPI - Version

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

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