# ggchivalrous/yiyin

一款照片水印添加工具

Repository: https://github.com/ggchivalrous/yiyin
Canonical: https://ross.abutalabs.com/products/yiyin
Language: TypeScript
License: GPL-3.0
License Family: copyleft
Last push: 2026-05-25T14:41:00+00:00

## Health v2 (maintenance only)
Score: 83/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 84, release rhythm 85, longevity 77
- inputs: {"age_days": 1089, "days_push": 100, "days_rel": 100, "gap_med": 13.5, "n_releases_24m": 5}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1703, forks 117 (observed 2026-08-28T04:05:24.502471+00:00)

## What it is
Yiyin (壹印) is a free, open-source desktop application for adding watermark frames to photos, generating styled image borders with customizable parameters and fonts. It works entirely offline with no embedded watermarks and supports custom font uploads stored locally.

## Use cases
- add watermark frames to photos before posting to social media
- generate styled photo borders with custom fonts
- batch process images to add signature frames
- convert portrait photos to landscape framed outputs
- brand photos with a personal watermark without online tools

## When to choose
- you want a free, offline, no-watermark photo framing tool
- you need customizable fonts and frame parameters for photo watermarks
- you prefer a simple install-and-use desktop app over web services

## When to avoid
- you need heavy image editing beyond watermarking and framing
- you require automated server-side or CLI batch pipelines
- you need fine-grained layer-based watermark positioning like professional editors

## Facets
- artifact type: application
- maturity: active
- function: image-processing
- domain: image-processing, photography, desktop-applications, media
- platform: cross-platform, windows
- tags: watermark, photo-frame, photography, batch-processing, custom-fonts, offline, desktop, macos

## Member repositories
- ggchivalrous/yiyin (main) score 83

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:24.502471+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:37:37.959657+00:00, confidence not recorded.
  - readme: https://github.com/ggchivalrous/yiyin (fetched 2026-08-28T04:05:24.502471+00:00, sha 20e0931e1dc2)
- Data as of 2026-08-30T08:39:29.467469+00:00.