What makes 图片抠图 Image Segmentation notable?

4.6K downloads. Trust evidence available

How should 图片抠图 Image Segmentation be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

图片抠图 Image Segmentation

Image matting tool: separates foreground from background and returns transparent background URL, suitable for product image processing, character cutout, and composition. 图像抠图工具：将前景与背景分离并返回透明背景的 URL，适用于产品图片处理、人物抠图和合成。 Skill: 图片抠图 Image Segmentation Owner: dlazyai Summary: Image matting tool: separates foreground from background and returns transparent background URL, suitable for product image processing, character cutout, and composition. 图像抠图工具：将前景与背景分离并返回透明背景的 URL，适用于产品图片处理、人物抠图和合成。 Tags: latest:1.3.26 Version history: v1.3.26 | 2026-10-08T01:15:52.913Z | user 例行版本更新 2026-10-08 v1.3.25 | 2026-10-04T01:14:45.109Z | user 例行版本更新 2

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

4.6k

Updated

Oct 9, 2026

Version

1.3.26

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 4.6K downloads reported by the source. Last updated 10/9/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 9, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 9, 2026
Adoption signal: 4.6K downloadsadoption · observed Oct 9, 2026
Latest release: 1.3.26release · observed Oct 8, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s170j1ymymrxasgd00dsk7tckx84cf45:dlazy-imageseg

Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-dlazyai-dlazy-imageseg/snapshot"

Documentation

CLAWHUB

148,549 characters of source documentation, loaded on request.

Extracted files

4 files captured from the source.

SKILL.md

---
name: dlazy-imageseg
version: 1.3.5
description: 'Image matting tool: separates foreground from background and returns transparent background URL, suitable for product image processing, character cutout, and composition. 图像抠图工具：将前景与背景分离并返回透明背景的 URL，适用于产品图片处理、人物抠图和合成。'
metadata: {"clawdbot":{"emoji":"🤖","requires":{"bins":["npm","npx"]},"install":"npm install -g @dlazy/[email protected]","installAlternative":"npx @dlazy/[email protected]","homepage":"https://github.com/dlazy-ai/cli","source":"https://github.com/dlazy-ai/cli","author":"dlazyai","license":"see-repo","npm":"https://www.npmjs.com/package/@dlazy/cli","configLocation":"~/.dlazy/config.json","apiEndpoints":["api.dlazy.com","files.dlazy.com"]},"openclaw":{"systemPrompt":"When invoking this skill, use dlazy imageseg -h for help."}}
---

# 图片抠图 Image Segmentation

[English](./SKILL.md) · [中文](./SKILL-cn.md)


Image matting tool: separates foreground from background and returns transparent background URL, suitable for product image processing, character cutout, and composition.

## Trigger Keywords

- imageseg

## Authentication

All requests require a dLazy API key. The recommended way to authenticate is:

```bash
dlazy login
```

This runs a device-code flow (also works in remote shells) and **automatically saves your API key** to the local CLI config — no manual copy/paste required.

### Alternative: Set the Key Manually

If you already have an API key, you can save it directly:

```bash
dlazy auth set YOUR_API_KEY
```

The CLI saves the key in your user config directory (`~/.dlazy/config.json` on macOS/Linux, `%USERPROFILE%\.dlazy\config.json` on Windows), with file permissions restricted to your OS user account. You can also supply the key per-invocation via the `DLAZY_API_KEY` environment variable.

### Getting Your API Key Manually

1. Sign in or create an account at [dlazy.com](https://dlazy.com)
2. Go to [dlazy.com/dashboard/organization/api-key](https://dlazy.com/dashboard/organization/api-key)
3. Copy the key shown in the API Key section

Each key is scoped to your dLazy organization and can be **rotated or revoked at any time** from the same dashboard.

## About & Provenance

- **CLI source code**: [github.com/dlazy-ai/cli](https://github.com/dlazy-ai/cli)
- **Maintainer**: dlazyai
- **npm package**: `@dlazy/cli` (pinned to `1.2.3` in this skill's install spec)
- **Homepage**: [dlazy.com](https://dlazy.com)

You can install on demand without persisting a global binary by running:

```bash
npx @dlazy/[email protected] <command>
```

Or, if you prefer a global install, the skill's `metadata.clawdbot.install` field declares the exact pinned version (`npm install -g @dlazy/[email protected]`). Review the GitHub source before installing.

## How It Works

This skill is a thin client over the dLazy hosted API. When you invoke it:

- Prompts and parameters you provide are sent to the dLazy API endpoint (`api.dlazy.com`) for inference.
- Any local f

_meta.json

{
  "ownerId": "kn7c5wgeajfcfvdfb5ceemvdb984cjpd",
  "slug": "dlazy-imageseg",
  "version": "1.3.26",
  "publishedAt": 1791422152913
}

skill-card.md

## Description:

Helps agents separate subjects from image backgrounds and return a transparent-background image URL for product photos, portraits, and compositions.

This skill is ready for commercial/non-commercial use.

## Publisher:

[dlazyai](https://clawhub.ai/user/dlazyai)

### License/Terms of Use:

MIT-0

## Use Case:

Creators and developers use this skill to cut out subjects from images for product listings, character assets, and compositing.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Images or local files supplied to the tool may be uploaded to dLazy, and generated images are hosted there.

Mitigation: Avoid submitting sensitive images unless dLazy hosting and processing are acceptable; review the pinned CLI package before use.

Risk: Authentication may save an API key in local configuration.

Mitigation: Use a per-invocation DLAZY_API_KEY when local key persistence is not desired.

## Reference(s):

- [ClawHub skill listing](https://clawhub.ai/dlazyai/skills/dlazy-imageseg)
- [dLazy CLI repository (linked in skill metadata)](https://github.com/dlazy-ai/cli)
- [dLazy CLI npm package](https://www.npmjs.com/package/@dlazy/cli)
- [dLazy website](https://dlazy.com)

## Skill Output:

**Output Type(s):** [Shell commands, Guidance]

**Output Format:** [Markdown instructions with shell examples; tool response contains JSON with an image URL]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Transparent PNG result URL; optional local download]

## Skill Version(s):

1.3.26 (source: ClawHub release metadata; artifact frontmatter lists 1.3.5)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

SKILL-cn.md

---
name: dlazy-imageseg
version: 1.3.5
description: '图像抠图工具：将前景与背景分离并返回透明背景的 URL，适用于产品图片处理、人物抠图和合成。'
metadata: {"clawdbot":{"emoji":"🤖","requires":{"bins":["npm","npx"]},"install":"npm install -g @dlazy/[email protected]","installAlternative":"npx @dlazy/[email protected]","homepage":"https://github.com/dlazy-ai/cli","source":"https://github.com/dlazy-ai/cli","author":"dlazyai","license":"see-repo","npm":"https://www.npmjs.com/package/@dlazy/cli","configLocation":"~/.dlazy/config.json","apiEndpoints":["api.dlazy.com","files.dlazy.com"]},"openclaw":{"systemPrompt":"当调用此技能时，可以使用 dlazy imageseg -h 查看帮助信息。"}}
---

# 图片抠图 Image Segmentation

[English](./SKILL.md) · [中文](./SKILL-cn.md)


图像抠图工具：将前景与背景分离并返回透明背景的 URL，适用于产品图片处理、人物抠图和合成。

## 触发关键词

- imageseg

## 身份验证 (Authentication)

所有请求都需要 dLazy API key。**推荐使用** `dlazy login` 完成登录：

```bash
dlazy login
```

该命令使用设备码流程（远程终端也可用），登录成功后 **自动把 API key 写入本地 CLI 配置**，无需手动复制粘贴。

### 备选：手动设置 API Key

如果你已有 API key，也可以直接保存：

```bash
dlazy auth set YOUR_API_KEY
```

CLI 会把 key 保存在你的用户配置目录（macOS/Linux 上为 `~/.dlazy/config.json`，Windows 上为 `%USERPROFILE%\.dlazy\config.json`），文件权限仅限当前操作系统用户访问。你也可以用 `DLAZY_API_KEY` 环境变量按次传入。

### 手动获取 API Key

1. 登录或在 [dlazy.com](https://dlazy.com) 创建账号
2. 访问 [dlazy.com/dashboard/organization/api-key](https://dlazy.com/dashboard/organization/api-key)
3. 复制 API Key 区域显示的密钥

每个 key 都属于你自己的 dLazy 组织，可在同一控制面板**随时轮换或吊销**。

## 关于与来源 (Provenance)

- **CLI 源代码**: [github.com/dlazy-ai/cli](https://github.com/dlazy-ai/cli)
- **维护者**: dlazyai
- **npm 包名**: `@dlazy/cli`（本技能 install 字段固定到 `1.2.3` 版本）
- **官网**: [dlazy.com](https://dlazy.com)

如果你不希望在系统上长期保留一个全局 CLI，可以按需运行：

```bash
npx @dlazy/[email protected] <command>
```

如选择全局安装，技能的 `metadata.clawdbot.install` 字段已固定到 `npm install -g @dlazy/[email protected]`。安装前建议先到 GitHub 仓库审阅源码。

## 工作原理

此技能是 dLazy 托管 API 的轻量封装。调用时：

- 你提供的提示词与参数会发送到 dLazy API（`api.dlazy.com`）进行推理。
- 传入图像 / 视频 / 音频字段的本地文件路径会被 CLI 上传到 dLazy 媒体存储（`files.dlazy.com`），以便模型读取 —— 与任何云端生成 API 的流程一致。
- API 返回的生成结果 URL 由 `files.dlazy.com` 托管。

这是标准的 SaaS 调用模式；技能本身不会越权访问网络或文件系统，所有动作都由 dLazy CLI 完成。完整服务条款请参见 [dlazy.com](https://dlazy.com)。

## 使用方法

**CRITICAL INSTRUCTION FOR AGENT**:
执行 `dlazy imageseg` 命令获取结果。

```bash
dlazy imageseg -h

Options:
  --image [image]                      图片链接 [image: url or local path]
  --dry-run                            Print payload + cost estimate without calling API
  --no-wait                            Return generateId immediately for async tasks
  --timeout <seconds>                  Max seconds to wait for async completion (default: "1800")
  --save <path>                        Download the result asset to this local path (mkdir + retry handled for you)
  -h, --help                           display help for command
```

> Any flag also accepts pipe references — `-` (auto-pick from upstream stdin), `@N` (n-th output), `@N.path` (jsonpath into output), `@*` (all primary values), `@stdi

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