Image Cropper

Crop objects from images using bounding box annotations in COCO, YOLO, VOC, or LabelMe formats with optional padding and batch processing.

Crop images based on bounding box annotations. Supports COCO, YOLO, VOC, and LabelMe formats. Use when user needs to extract objects from images based on annotation boxes.

Features

• Multi-format Support: COCO, YOLO, VOC, LabelMe
• Batch Processing: Crop entire datasets
• Padding: Add padding around bounding boxes
• Output Options: Individual files or sprite sheet
• Handle Missing: Gracefully handle images without annotations

Usage

# Crop YOLO annotations
python scripts/cropper.py yolo images/ labels/ output/

# Crop COCO annotations
python scripts/cropper.py coco annotations.json images/ output/

# Crop with padding
python scripts/cropper.py yolo images/ labels/ output/ --padding 10

# Crop all objects to individual files
python scripts/cropper.py yolo images/ labels/ output/ --objects

Examples

$ python scripts/cropper.py yolo ./images ./labels ./output

Processing 100 images...
✓ Cropped 250 objects from image_001.jpg
✓ Cropped 180 objects from image_002.jpg
...
Total: 500 cropped images

Installation

pip install pillow

Options

• --padding: Padding around box (pixels, default: 0)
• --objects: Save each object as separate file
• --min-size: Minimum box size to crop (pixels)
• --format: Output format (jpg, png, default: jpg)
• --quality: JPEG quality 1-100 (default: 95)