DeepSeek Harness plugin

dsh-imagedit

Local image editing toolkit for DeepSeek Harness: one image_edit tool for deterministic edits — cutout (quick flood-fill or rembg AI), trim, flip, rotate, brightness/contrast/saturation, blur

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Source facts

Repository
bbbz123/dsh-imagedit
Latest update
Aug 20, 2026
Category
Tools & Capabilities
GitHub stars
0
Format
plugin
Catalog evidence
Upstream dsh.bundle evidence
Evidence path
package.json#dsh.bundle
Checked against
0.1.0-rc.8
Upstream check date
2026-08-21

This evidence comes from the upstream catalog. This site has not installed, run, or security-reviewed the plugin.

Install

Start with a prompt that asks an agent to review the GitHub repository and source. Switch to the command if you want to install it yourself.

Copy this prompt into DSH, Codex, or another agent and ask it to review the GitHub repository and source first.

Do not install or run any commands yet. Read this plugin's GitHub repository, README, and relevant source code. Then answer the questions below clearly and directly so I can decide whether it fits my needs:

1. What is this plugin, and what problem does it solve?
2. Who is it for, and what are its typical use cases?
3. How is it used after installation? Include one minimal example.
4. What known limitations or privacy, security, compatibility, or maintenance risks does it have?
5. Give a clear recommendation: recommend, conditionally recommend, or do not recommend, with reasons.

Distinguish statements documented by the repository, inferences from source code, and unknowns. If evidence is insufficient, say so explicitly. Do not guess or simply repeat the README.

GitHub: https://github.com/bbbz123/dsh-imagedit
Plugin: dsh-imagedit
Author: bbbz123

Check the source files

Read the README and other files from this plugin directory before installing.

File explorer3 files
README.mdSource · read only

dsh-imagedit

本地图像编辑工具箱 — A DeepSeek Harness (DSH) plugin and skill for deterministic local image editing: background cutout (rembg AI or instant flood-fill), trim, flip, rotate, brightness/contrast/saturation, blur, sharpen, rounded corners, border, canvas normalization, sprite sheets, and PNG/JPEG/WebP export.

Dual form: a cordis plugin that registers an image_edit agent tool (agent calls it directly with structured parameters), and a skill with the same functionality via a Python CLI. Originally adapted from a Codex skill and upgraded for DSH (dependency-free quick cutout, sprite sheets, JPEG export, batch-directory processing).

Features

AreaOperations
抠图remove_bg: quick (flood-fill, no model) · remove_bg: rembg (AI)
基础trim · flip h/v · rotate · padding · canvas WxH (scale+center)
调色brightness · contrast · saturation
滤镜blur · sharpen
修饰rounded (corners) · border W[,HEX] · auto-orient (EXIF)
批量JSON manifest · --dir recursive folder · sprite sheet + sprites.json
导出PNG (oxipng/pngquant auto) · JPEG · WebP (quality)

Install

As a plugin (agent tool image_edit) — recommended

# local link install
dsh plugin --profile web add link:D:\path\to\dsh-imagedit

# once published on npm / GitHub
dsh plugin --profile web add dsh-imagedit
# or
dsh plugin --profile web add github:bbbz123/dsh-imagedit

Restart dsh web; the image_edit tool then appears in the tool catalog and the agent can call it directly. Override the Python interpreter with the DSH_IMAGEDIT_PYTHON environment variable if needed.

As a skill (CLI)

git clone https://github.com/bbbz123/dsh-imagedit "$HOME\.dsh\skills\dsh-imagedit"
# or copy the folder into <project>\.dsh\skills\dsh-imagedit for one project

DSH discovers it automatically. The skill instructs the agent to prefer the image_edit tool when available and fall back to the CLI.

Usage

Agent tool

Call image_edit with structured params, e.g.:

{
  "input": "gen/sword.png",
  "remove_bg": "quick",
  "bg_color": "auto",
  "canvas": "256x256",
  "padding": 16,
  "formats": ["png", "webp"]
}

CLI

# quick flood-fill cutout + canvas
python scripts/asset_pipeline.py run --input item.png `
  --remove-bg-quick auto --canvas 256x256 --padding 16 --out-dir output/images/edited

# combined edits
python scripts/asset_pipeline.py run --input item.png `
  --remove-bg-quick #FFFFFF --rotate 90 --flip h `
  --brightness 1.1 --saturation 1.2 --rounded 30 --border "4,#FF0000" `
  --exports png jpg --out-dir output/images/edited

# batch a whole folder (recursive)
python scripts/asset_pipeline.py batch --dir ./photos --rotate 90 --exports jpg

# batch manifest + sprite sheet
python scripts/asset_pipeline.py batch --manifest manifest.json

See [references/cli.md](references/cli.md) for the full CLI reference and manifest schema, and SKILL.md for the agent-facing instructions.

Recommended pipeline (with dsh-draw + vision-router)

dsh-draw / image_generate  (prompt: "flat solid white background, no shadows")
  → image_edit (remove_bg: quick, canvas, padding)  →  engine-ready PNG
  → batch manifest with "sheet" for a sprite atlas

For complex assets prefer remove_bg: "rembg"; for one-off visual checks of the cutout use vision_extract_foreground.

Requirements

  • Python 3.10+ and Pillow (required)
  • rembg (optional, only for the rembg cutout mode)
  • oxipng / pngquant (optional, auto-used when on PATH)

License

MIT — see [LICENSE](LICENSE).