{
  "added_at": "2026-11-08",
  "additional_evidence_urls": [
    "https://github.com/rohanpandula/upright/blob/490391d43f57f802ba278062c69670333655ec4e/README-validation.md",
    "https://github.com/rohanpandula/upright/blob/490391d43f57f802ba278062c69670333655ec4e/port/README.md"
  ],
  "category": "reconstruction-cases",
  "class": "software",
  "description_en": "upright reconstructs Lightroom Classic's Upright perspective correction from catalog transforms, controlled application runs, and selected CameraRaw binary observations. It publishes a two-camera homography model, measured Auto-mode behavior, evidence files, and an MIT-licensed Python port; the author reports that the port performs poorly on real photographs.",
  "description_zh": "upright 根据 Lightroom Classic 目录中的变换、受控应用运行结果及 CameraRaw 二进制的部分观察，重建 Upright 透视校正。仓库提供双相机单应变换模型、Auto 模式的测量结果、证据文件和 MIT 许可的 Python 移植版；作者报告移植版在真实照片上表现较差。",
  "entry_url": "https://awesomerea.org/resources/lightroom-upright-case/",
  "entry_url_zh": "https://awesomerea.org/zh/resources/lightroom-upright-case/",
  "evidence_class": 2,
  "evidence_status": "observed",
  "evidence_url": "https://github.com/rohanpandula/upright/blob/490391d43f57f802ba278062c69670333655ec4e/README.md",
  "group": "cases",
  "id": "lightroom-upright-case",
  "json_url": "https://awesomerea.org/resources/lightroom-upright-case/record.json",
  "kind": "case-study",
  "markdown_url": "https://awesomerea.org/resources/lightroom-upright-case/index.md",
  "markdown_url_zh": "https://awesomerea.org/zh/resources/lightroom-upright-case/index.md",
  "name": "upright: reconstructing Lightroom Classic's perspective correction",
  "name_zh": "upright：重建 Lightroom Classic 的透视校正",
  "record_type": "resource",
  "relationship": "independent-reconstruction",
  "requirement_facets": [
    "prerequisites",
    "limits",
    "license"
  ],
  "requirements": [
    "Python 3.10 or newer, NumPy, and OpenCV are needed for the port.",
    "The author reports that the port often returns identity on real photos and has a 40.7% loss rate against plain identity in the stated comparison.",
    "MIT License."
  ],
  "requirements_zh": [
    "运行移植版需要 Python 3.10 或更高版本、NumPy 和 OpenCV。",
    "作者报告，移植版处理真实照片时常返回恒等变换；在所述比较中，相对不校正的失利比例为 40.7%。",
    "采用 MIT 许可证。"
  ],
  "scope": "unknown",
  "targets": [
    "app",
    "binary"
  ],
  "url": "https://github.com/rohanpandula/upright",
  "verification": "source-reviewed",
  "verified_at": "2026-11-06"
}