Siddharth Kumar Sah 3c1bf0a77d feat(ai): dual-model face detection with NMS deduplication
Run both short-range and full-range MediaPipe models and merge results,
then apply non-maximum suppression to remove duplicate bounding boxes.
Fixes missed faces in group photos where the single-model loop exited
early after the first positive detection.
2026-04-15 23:11:36 +08:00
2026-04-03 23:17:06 +08:00
2026-04-15 09:17:07 +08:00

We've renamed! Formerly Stirling Image, now ashim.
github.com/ashim-hq/ashim

ashim logo

ashim

ashim but for images. 30+ tools and local AI in a single Docker container.

Docker CI License Stars

ashim - Dashboard

Key Features

  • 30+ image tools - Resize, crop, compress, convert, watermark, color adjust, and more
  • Local AI - Remove backgrounds, upscale images, erase objects, blur faces, extract text (OCR). All running on your hardware with pre-downloaded models, no internet required
  • Pipelines - Chain tools into reusable workflows. Batch process up to 200 images at once
  • REST API - Every tool available via API. Interactive docs included at /api/docs
  • Single container - One docker run, no Redis, no Postgres, no external services
  • Multi-arch - Runs on AMD64 and ARM64 (Intel, Apple Silicon, Raspberry Pi)
  • Your data stays yours - No telemetry, no tracking, no external calls. Images never leave your machine

Quick Start

docker run -d -p 1349:1349 -v ashim-data:/data stirlingimage/stirling-image:latest

Open http://localhost:1349 in your browser.

Have an NVIDIA GPU? Click here for GPU acceleration.

Add --gpus all for GPU-accelerated background removal, upscaling, and OCR:

docker run -d -p 1349:1349 --gpus all -v ashim-data:/data stirlingimage/stirling-image:latest 

Requires an NVIDIA GPU and Container Toolkit. Falls back to CPU if no GPU is found. See Docker Tags for benchmarks and Docker Compose examples.

Default credentials:

Field Value
Username admin
Password admin

You will be asked to change your password on first login. This is enforced for all new accounts and cannot be skipped in production.

For Docker Compose, persistent storage, and other setup options, see the Getting Started Guide. For GPU acceleration and tag details, see Docker Tags.

Documentation

Feedback

Found a bug or have a feature idea? Open a GitHub Issue. We don't accept pull requests, but your feedback directly shapes the project. See CONTRIBUTING.md for details.

License

This project is dual-licensed under the AGPLv3 and a commercial license.

  • AGPLv3 (free): You may use, modify, and distribute this software under the AGPLv3. If you run a modified version as a network service, you must make your source code available under the AGPLv3. This applies to personal use, open-source projects, and any use that complies with AGPLv3 terms.
  • Commercial license (paid): If you want to use ashim in proprietary software or SaaS without the AGPLv3 source-disclosure requirement, a commercial license is available. Contact me for pricing and terms.
Languages
TypeScript 91%
Python 3.5%
JavaScript 2.4%
Shell 1.6%
Astro 1.1%
Other 0.3%