# Tree Disk Segmentation
[](https://pypi.org/project/tree-disk-segmentation/)
A Python package for analyzing tree rings in cross-sectional images.
## Installation
```bash
pip install tree-disk-segmentation
```
## Usage
### Python API
```python
import treedisksegmentation
# Configure the analyzer
treedisksegmentation.configure(
input_image="input/tree-disk4.png",
save_results=True,
)
# Run the segmentation
(
result_image, # Image with detected tree disks
masks, # List of masks for each detected tree disk
) = treedisksegmentation.run()
```
### Command Line Interface (CLI)
Basic usage:
```bash
tree-disk-segmentation --input_image ./input/baumscheibe.jpg --output_dir ./output
```
Save intermediate results:
```bash
tree-disk-segmentation --input_image ./input/baumscheibe.jpg --output_dir ./output --model_path ./models/yolo11s-seg-tree.pt --save_results
```
## CLI Arguments
| Argument | Type | Required | Default | Description |
|----------|------|----------|---------|-------------|
| `--input_image` | str | Yes | - | Path to input image |
| `--output_dir` | str | No | `./output` | Output directory path |
| `--model_path` | str | No | `./models/yolo11s-seg-tree.pt` | Path to the pre-trained model weights |
| `--debug` | flag | No | False | Enable debug mode |
| `--save_results` | flag | No | False | Save intermediate images, labelme and config file |
## Development
### Setting up Development Environment
1. Create and activate virtual environment:
```bash
poetry config virtualenvs.in-project true
poetry env use python
```
```bash
poetry install
eval $(poetry env activate)
```
2. Running tests:
```bash
poetry run pytest
```
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