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Install in OpenClaw
/install image-cropper
Description
Crop objects from images using bounding box annotations in COCO, YOLO, VOC, or LabelMe formats with optional padding and batch processing.
README (SKILL.md)
Image Cropper
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)
Usage Guidance
This skill appears to be a straightforward local image-cropping utility. Before installing or running it: (1) verify the full scripts/cropper.py file in the package (the preview in the prompt looked truncated); (2) run it in an environment where input images/labels are from trusted sources (it reads and writes local files only); (3) install Pillow from PyPI in a virtual environment (pip install pillow); (4) if you need stronger assurance, quickly grep the script for network/socket/requests/imports to confirm there are no external endpoints or hidden code paths; and (5) consider running initial tests on a small dataset to confirm behavior and outputs.
Capability Analysis
Type: OpenClaw Skill
Name: image-cropper
Version: 1.0.0
The skill bundle provides a legitimate utility for cropping images based on common object detection annotation formats (YOLO, COCO, VOC). The implementation in `scripts/cropper.py` uses standard libraries such as `PIL` for image manipulation and `pathlib` for file handling, with logic that is clearly aligned with the stated purpose. No malicious behaviors, data exfiltration, or prompt injection attempts were detected in the code or the `SKILL.md` instructions.
Capability Assessment
Purpose & Capability
Name/description match the included script and SKILL.md. The tool only requires Pillow (documented in SKILL.md) and operates on local image and annotation files (COCO/YOLO/VOC/LabelMe).
Instruction Scope
SKILL.md instructs running the included script with local paths and options (padding, objects, format). The instructions do not ask the agent to read unrelated system files, environment variables, or to transmit data externally. Note: the printed code excerpt in the manifest appears truncated in the prompt display, but the file manifest indicates a full script is present — verify the full file if you plan to install.
Install Mechanism
No install spec; SKILL.md recommends 'pip install pillow' which is appropriate for the script. No downloads from arbitrary URLs or archive extraction are present.
Credentials
No environment variables, credentials, or config paths are required. The script does not access secrets or external services in the provided code.
Persistence & Privilege
Skill does not request always:true or any elevated/system-wide privileges; it is user-invocable only and does not modify other skill configurations.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install image-cropper - After installation, invoke the skill by name or use
/image-cropper - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of image-cropper.
- Crop images using bounding box annotations in COCO, YOLO, VOC, and LabelMe formats
- Batch process entire datasets with optional padding around bounding boxes
- Output cropped objects as individual files or as a sprite sheet
- Optionally filter by minimum box size and select output format and JPEG quality
- Gracefully handle images without annotations
Metadata
Frequently Asked Questions
What is Image Cropper?
Crop objects from images using bounding box annotations in COCO, YOLO, VOC, or LabelMe formats with optional padding and batch processing. It is an AI Agent Skill for Claude Code / OpenClaw, with 309 downloads so far.
How do I install Image Cropper?
Run "/install image-cropper" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Image Cropper free?
Yes, Image Cropper is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Image Cropper support?
Image Cropper is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Image Cropper?
It is built and maintained by Mingo_318 (@mingo-318); the current version is v1.0.0.
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