# argus-cv

Vision AI dataset toolkit for working with YOLO, COCO, and semantic mask datasets.

**[Documentation](https://pirnerjonas.github.io/argus/)**

Library users can start with the Python API reference:

- https://pirnerjonas.github.io/argus/reference/python-api/

## Installation

```bash
uvx argus-cv
```

## Highlights

- Detects YOLO, COCO, and folder-based semantic mask datasets.
- Reports per-class stats (pixel coverage for mask datasets).
- Interactive viewer with bounding boxes, polygons, or mask overlays.
- Split and unsplit YOLO/COCO/mask datasets.

## Usage

```bash
# List datasets in current directory
uvx argus-cv list

# List datasets in specific path
uvx argus-cv list --path /path/to/datasets

# Limit search depth
uvx argus-cv list --path . --max-depth 2

# Show instance statistics for a dataset
uvx argus-cv stats /path/to/dataset

# View annotations interactively
uvx argus-cv view /path/to/dataset --split val

# Split an unsplit dataset into train/val/test
uvx argus-cv split /path/to/dataset -o /path/to/output -r 0.8,0.1,0.1

# Merge a split dataset back into unsplit layout
uvx argus-cv unsplit -d /path/to/split_dataset -o /path/to/output

# Filter dataset to selected classes
uvx argus-cv filter /path/to/dataset -o /path/to/output --classes person,car

# Convert mask -> YOLO segmentation
uvx argus-cv convert -i /path/to/masks -o /path/to/output --to yolo-seg
```
