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Star Trek Online screenshot recognition + ML training (standalone WARP/WARP CORE).

Project description

STO-WARP

Star Trek Online screenshot recognition + ML training, distributed as a standalone Python package.

What is this?

STO-WARP combines two tools in one package:

WARP (Weaponry & Armament Recognition Platform) — reads your in-game screenshots and automatically fills in your SETS build. Detects equipment, traits, bridge officers, and ship information using computer vision and machine learning.

WARP CORE — trainer interface built into WARP. Review and correct recognition results, confirm annotations, and retrain the local ML models (Icon Classifier + Layout Regressor) on your own data to improve accuracy over time.

Technology

  • WARP — recognition pipeline (OCR + layout detection + icon matching). Reads STO screenshots and emits structured slot/item results.
  • WARP CORE — Qt trainer UI for reviewing recognition output and fine-tuning the EfficientNet / MobileNetV3 models that drive WARP.

Install

The recommended way to install sto-warp is via our universal installation scripts, which will automatically configure an isolated environment using pipx.

Linux / macOS:

curl -sSL https://raw.githubusercontent.com/raman78/sto-warp/main/install.sh | bash

Windows (PowerShell):

Invoke-WebRequest -Uri "https://raw.githubusercontent.com/raman78/sto-warp/main/install.ps1" -OutFile "install.ps1"; .\install.ps1; Remove-Item "install.ps1"

On first launch sto-warp registers itself in your system menu — Start Menu on Windows, Launchpad / Spotlight on macOS, Activities / KRunner on Linux — so subsequent runs can be started by clicking the icon instead of opening a terminal.

For manual installation methods and more details, see INSTALLATION.md.

Data and models

On first run sto-warp downloads:

  • ML models (icon_classifier.pt, screen_classifier.pt) from the Hugging Face hub.
  • Cargo / ship / trait JSON from the community STOCD/SETS-Data repository.
  • Community knowledge (knowledge.json), admin icon equivalence map, and a seed tarball of confirmed crops.

A small setup splash blocks the launcher on the very first start until all of the above finish, so the application opens with a complete data set. On every later run the cache is refreshed silently in the background. Everything is cached under ~/.config/warp/ (or $XDG_CONFIG_HOME/warp/ when set). Nothing is committed to this repository. See docs/WARP_GUIDE.md for the user-facing walkthrough and docs/SYNC_ARCHITECTURE.md for the technical view.

License

GPL-3.0 — see LICENSE.

Project docs

  • INSTALLATION.md — install methods (pipx, native packages).
  • CHANGELOG.md — release notes.
  • PROJECT_CONTEXT.md — design context.
  • CLAUDE.md — repository rules for AI-assisted development.
  • docs/ — technical deep-dives (BOFF / trait detection, ML pipeline, …).

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