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
| Area | Operations |
|---|
| 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 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.
