# Tree Disk Pith Detection
[](https://pypi.org/project/tree-disk-pith/)
A Python package for analyzing tree rings in cross-sectional images. Originally forked from [hmarichal93/apd](https://github.com/hmarichal93/apd).
## Installation
```bash
pip install tree-disk-pith
```
## Usage
### Python API
```python
import treediskpith
# Configure the analyzer
treediskpith.configure(
input_image="input/tree-disk4.png",
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:
```bash
tree-disk-pith --input_image ./input/tree-disk3.png --new_shape 640 --debug
```
Save intermediate results:
```bash
tree-disk-pith --input_image ./input/tree-disk3.png --new_shape 640 --debug --method apd_pcl --save_results
```
Advanced usage with custom parameters:
```bash
tree-disk-pith \
--input_image input/tree-disk3.png \
--cx 1204 \
--cy 1264 \
--output_dir custom_output/ \
--sigma 4.0 \
--th_low 10 \
--th_high 25 \
--save_results \
--debug
```
## CLI Arguments
| Argument | Type | Required | Default | Description |
|----------|------|----------|---------|-------------|
| `--input_image` | str | Yes | - | Input image file path |
| `--output_dir` | str | Yes | - | Output directory path |
| `--method` | str | No | apd | Detection method to use. Choices are apd, apd_pcl, or apd_dl |
| `--model_path` | str | No | - | Path to the weights file (required if using apd_dl method) |
| `--percent_lo` | float | No | 0.7 | percent_lo parameter for the algorithm |
| `--st_w` | int | No | 3 | st_w parameter for the algorithm |
| `--lo_w` | int | No | 3 | lo_w parameter for the algorithm |
| `--st_sigma` | float | No | 1.2 | st_sigma parameter for the algorithm |
| `--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. Clone the repository:
```bash
git clone https://github.com/tuke307/tree-disk-pith.git
cd tree-disk-pith
```
2. Create and activate virtual environment:
```bash
poetry install
poetry shell
```
3. fetch dataset
```bash
python fetch_dataset.py
```
4. Download pretrained model
```bash
python fetch_pretrained_model.py
```
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"description": "# Tree Disk Pith Detection\n\n[](https://pypi.org/project/tree-disk-pith/)\n\nA Python package for analyzing tree rings in cross-sectional images. Originally forked from [hmarichal93/apd](https://github.com/hmarichal93/apd).\n\n## Installation\n\n```bash\npip install tree-disk-pith\n```\n\n## Usage\n\n### Python API\n\n```python\nimport treediskpith\n\n# Configure the analyzer\ntreediskpith.configure(\n input_image=\"input/tree-disk4.png\",\n save_results=True,\n)\n\n# Run the detection\n(\n img_in, # Original input image\n img_pre, # Preprocessed image\n pith, # Center of the tree disk\n) = treediskpith.run()\n```\n\n### Command Line Interface (CLI)\n\nBasic usage:\n```bash\ntree-disk-pith --input_image ./input/tree-disk3.png --new_shape 640 --debug\n```\n\nSave intermediate results:\n```bash\ntree-disk-pith --input_image ./input/tree-disk3.png --new_shape 640 --debug --method apd_pcl --save_results\n```\n\nAdvanced usage with custom parameters:\n```bash\ntree-disk-pith \\\n --input_image input/tree-disk3.png \\\n --cx 1204 \\\n --cy 1264 \\\n --output_dir custom_output/ \\\n --sigma 4.0 \\\n --th_low 10 \\\n --th_high 25 \\\n --save_results \\\n --debug\n```\n\n## CLI Arguments\n\n| Argument | Type | Required | Default | Description |\n|----------|------|----------|---------|-------------|\n| `--input_image` | str | Yes | - | Input image file path |\n| `--output_dir` | str | Yes | - | Output directory path |\n| `--method` | str | No | apd | Detection method to use. Choices are apd, apd_pcl, or apd_dl |\n| `--model_path` | str | No | - | Path to the weights file (required if using apd_dl method) |\n| `--percent_lo` | float | No | 0.7 | percent_lo parameter for the algorithm |\n| `--st_w` | int | No | 3 | st_w parameter for the algorithm |\n| `--lo_w` | int | No | 3 | lo_w parameter for the algorithm |\n| `--st_sigma` | float | No | 1.2 | st_sigma parameter for the algorithm |\n| `--new_shape` | int | No | 0 | New shape for resizing the input image. If 0, no resizing is done |\n| `--debug` | flag | No | False | Enable debug mode to save intermediate images and outputs |\n| `--save_results` | flag | No | False | Save intermediate images, labelme and config file |\n\n## Development\n\n### Setting up Development Environment\n\n1. Clone the repository:\n```bash\ngit clone https://github.com/tuke307/tree-disk-pith.git\ncd tree-disk-pith\n```\n\n2. Create and activate virtual environment:\n```bash\npoetry install\npoetry shell\n```\n\n3. fetch dataset\n```bash\npython fetch_dataset.py\n```\n\n4. Download pretrained model\n```bash\npython fetch_pretrained_model.py\n```\n\n",
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