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argus-cv

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

Documentation

Library users can start with the Python API reference:

Installation

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

# 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

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