风险评分

94/100 (Very Low)

OpenClaw: benign
VirusTotal: benign
StaticScan: unknown

Image Cropper

作者: Mingo_318
Slug:image-cropper
版本:1.0.0
更新时间:2026-03-05 19:59:24
风险信息

OpenClaw: benign

查看 OpenClaw 分析摘要
The skill's code, instructions, and requirements are consistent with a simple image-cropping utility and do not request unrelated credentials or network access.

VirusTotal: benign VT 报告

静态扫描: unknown

README

README 未提供

文件列表

无文件信息

下载
下载官方 ZIP
原始 JSON 数据
{
    "latestVersion": {
        "_creationTime": 1772711934238,
        "_id": "k97dzstbwn0d34h95y1xygzfyx82bpaj",
        "changelog": "Initial release of image-cropper.\n\n- Crop images using bounding box annotations in COCO, YOLO, VOC, and LabelMe formats\n- Batch process entire datasets with optional padding around bounding boxes\n- Output cropped objects as individual files or as a sprite sheet\n- Optionally filter by minimum box size and select output format and JPEG quality\n- Gracefully handle images without annotations",
        "changelogSource": "auto",
        "createdAt": 1772711934238,
        "version": "1.0.0"
    },
    "owner": {
        "_creationTime": 0,
        "_id": "publishers:missing",
        "displayName": "Mingo_318",
        "handle": "mingo-318",
        "image": "https:\/\/avatars.githubusercontent.com\/u\/62329898?v=4",
        "kind": "user",
        "linkedUserId": "kn70b530db30wxzakwkzdejfd582a9j3"
    },
    "ownerHandle": "mingo-318",
    "skill": {
        "_creationTime": 1772711934238,
        "_id": "kd7b153bjtt0hp81cjk9d3xpv182bxn1",
        "badges": [],
        "createdAt": 1772711934238,
        "displayName": "Image Cropper",
        "latestVersionId": "k97dzstbwn0d34h95y1xygzfyx82bpaj",
        "ownerUserId": "kn70b530db30wxzakwkzdejfd582a9j3",
        "slug": "image-cropper",
        "stats": {
            "comments": 0,
            "downloads": 190,
            "installsAllTime": 3,
            "installsCurrent": 3,
            "stars": 0,
            "versions": 1
        },
        "summary": "Crop objects from images using bounding box annotations in COCO, YOLO, VOC, or LabelMe formats with optional padding and batch processing.",
        "tags": {
            "latest": "k97dzstbwn0d34h95y1xygzfyx82bpaj"
        },
        "updatedAt": 1772711964220
    }
}