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YOLO Dataset Tools - Comprehensive toolkit for YOLO format dataset processing

Project description

YDT - YOLO Dataset Tools

Python VersionLicenseCode style: RuffType Checked

English | 简体中文

Features

  • Auto-detects and handles both OBB (9 values: class_id x1 y1 x2 y2 x3 y3 x4 y4) and BBox (5 values: class_id x_center y_center width height) formats
  • SAHI-powered smart slicing for large images with horizontal/grid modes and configurable overlap
  • Resize (scale & crop) with custom interpolation (linear/lanczos4),image or yolo dataset
  • Coordinate-based precision cropping
  • Video frame extraction with parallel processing support
  • Smart train/val split with class balancing
  • Multi-dataset merging
  • Dataset extraction by class IDs with optional label filtering and ID remapping
  • Synthetic dataset generation with configurable objects per image and rotation ranges
  • YOLO auto-labeling with BBox/OBB format support
  • Interactive dataset browser with keyboard controls (n/p/q)

Installation

pip install yolodt

Usage

ydt --help

usage: ydt [-h] [--version] [-v]
           {slice,augment,video,crop-coords,resize,concat,split,merge,extract,synthesize,auto-label,analyze,visualize,viz-letterbox}
           ...

YOLO Dataset Tools - Process and manage YOLO format datasets

positional arguments:
  {slice,augment,video,crop-coords,resize,concat,split,merge,extract,synthesize,auto-label,analyze,visualize,viz-letterbox}
                        Available commands
    slice               Slice large images into tiles
    augment             Augment dataset with rotations
    video               Extract frames from videos
    crop-coords         Crop images by coordinates
    resize              Resize images or YOLO dataset
    concat              Concatenate two images
    split               Split dataset into train/val
    merge               Merge multiple datasets
    extract             Extract classes, images, or labels
    synthesize          Generate synthetic dataset
    auto-label          Auto-label images using YOLO model
    analyze             Analyze dataset statistics
    visualize           Visualize YOLO dataset interactively
    viz-letterbox       Visualize letterbox transformation

options:
  -h, --help            show this help message and exit
  --version             show program's version number and exit
  -v, --verbose         Verbose output

🙏 Acknowledgments


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