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Releases: developer0hye/Yolo_Label

v3.1.1

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@developer0hye developer0hye released this 24 Feb 15:51
4b90f80

What's Changed

Bug Fixes

  • Fix: Load Model dialog too dark on Linux — The file dialog was unreadable (dark text on dark background) on platforms using Qt's fallback (non-native) file dialog. Fixed by passing nullptr instead of this as the parent, preventing the MainWindow dark stylesheet from cascading into the dialog. (#124)

Docs

  • Clarify that Ctrl+Arrow resize shortcut keeps the top-left corner fixed (#121)

Full Changelog: v3.1.0...v3.1.1

Contributors

Thanks to @dennisushi for reporting the dark dialog issue (#122).

What's Changed

Full Changelog: v3.1.0...v3.1.1

v3.1.0

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@developer0hye developer0hye released this 18 Feb 02:28
9821ecd

What's New

Bounding Box Resize via Keyboard (#120)

You can now resize bounding boxes using keyboard shortcuts without deleting and redrawing them:

Shortcut Action
Ctrl + Arrow Keys (Win/Linux) / Cmd + Arrow Keys (macOS) Resize box (~1-2px step)
Ctrl + Shift + Arrow Keys (Win/Linux) / Cmd + Shift + Arrow Keys (macOS) Resize box (~5px step)

The top-left corner stays fixed while the right/bottom edges adjust. Undo (Ctrl+Z / Cmd+Z) works as expected.

Documentation

  • Added EfficientSAM3 analysis to SAM document (#119)
  • Added SAM pseudo labeling analysis (#118)
  • Updated README for macOS signed distribution (#117)

Full Changelog: v3.0.0...v3.1.0

What's Changed

Full Changelog: v3.0.0...v3.1.0

v3.0.0

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@github-actions github-actions released this 17 Feb 15:40
4884729

What's New in v3.0.0

Auto-Label (Pseudo Labeling) — The Headline Feature

Tired of drawing every single bounding box by hand? v3.0.0 introduces local YOLO inference powered by ONNX Runtime. Export any Ultralytics detection model to .onnx, load it into YOLO-Label, and let the model do the heavy lifting.

  • One-file setup — A single .onnx file is all you need. Class names, input size, and model configuration are all read from the ONNX metadata automatically. No separate config files, no manual setup.
  • Supported models — YOLOv5, YOLOv8, YOLO11, YOLO12, YOLOv26, and end-to-end models (NMS baked in). Any current and future Ultralytics detection model that follows the same ONNX export format should just work.
  • Per-image or batch processing — Click Auto Label (or press R) to detect objects on the current image, or Auto Label All to batch-process every image in the dataset.
  • Adjustable confidence threshold — Use the slider to control detection sensitivity (default 25%).
  • Fully editable results — Auto-labeled boxes can be moved, deleted, class-changed, or undone (Ctrl+Z) using all existing annotation tools.
  • Class list mismatch warning — If the loaded model's class list doesn't match the current dataset's class file, YOLO-Label warns you and disables auto-labeling to prevent incorrect annotations.
  • Skip class file entirely — If the model has embedded class names (all Ultralytics exports do), they will be loaded automatically. You can launch with just an image directory and an ONNX model.
  • CLI support — Pass the .onnx file as a command-line argument: ./YoloLabel [dataset dir] [class file] [model.onnx]. Arguments are detected by file extension.
  • Conditional build — ONNX Runtime is optional. Without it, the app builds and works normally — just without the auto-label feature. Pre-built releases include ONNX Runtime.

macOS Code Signing & Notarization

macOS builds are now signed with a Developer ID certificate and notarized by Apple. This means:

  • No more Gatekeeper warnings — Download the DMG, open it, drag YoloLabel to Applications, and it just works. No need to right-click → Open or disable Gatekeeper.
  • Inside-out code signing — All nested frameworks, dylibs, and plugins are individually signed per Apple's current requirements (macOS 13+), with hardened runtime enabled.
  • Notarized on release — Release DMGs are submitted to Apple's notary service and stapled, so Gatekeeper can verify them even offline.
  • Entitlements — Minimal entitlements (allow-unsigned-executable-memory, disable-library-validation) are applied only to the main executable for Qt and ONNX Runtime compatibility.

Other Improvements

  • Default file dialog to application directory — File open dialogs now start at the application's directory instead of the system default, making it easier to find your datasets and models (#112)
  • Bundled COCO class names — A coco_names.txt file is included in the Samples directory for quick testing with COCO-trained models (#112)

Bug Fixes

  • Fixed wheel scroll on class table changing images — Scrolling the mouse wheel over the class label table no longer accidentally navigates to the next/previous image (#111)
  • Fixed UTF-8 model path on Windows — ONNX model files in directories with non-ASCII characters (e.g., Korean, Chinese, Japanese) now load correctly on Windows by using std::filesystem::path for proper wide-string conversion (#113)
  • Fixed dynamic-shape ONNX model handling — Models exported without fixed input dimensions are now handled correctly by reading the imgsz metadata field
  • Fixed out-of-bounds read in image preprocessing — Resolved a scanline indexing bug that could cause crashes or incorrect inference on certain image sizes

Internal / CI

  • Removed dead code for previously deleted save/remove buttons (#109)
  • Added CI accuracy test that compares C++ inference output against Ultralytics Python reference to catch regressions
  • macOS CI: inside-out code signing, Developer ID signing + notarization pipeline (#116)

Downloads

OS File Notes
Windows (x64) YoloLabel-Windows-x64.zip Unzip and run YoloLabel.exe
Linux (x64) YoloLabel-Linux-x64.AppImage chmod +x and run
macOS (Apple Silicon) YoloLabel-macOS.dmg Signed & notarized — open DMG and drag to Applications

What's Changed

Full Changelog: v2.0.0...v3.0.0

v0.0.1-experimental

v0.0.1-experimental Pre-release
Pre-release

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What's Changed

Full Changelog: v3.0.0...v0.0.1-experimental

v2.0.0

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@github-actions github-actions released this 14 Feb 06:38
82834ec

What's New in v2.0.0

A major update built on Qt 6 with automated CI/CD builds for Windows, Linux, and macOS.

Framework & Infrastructure

  • Migrated from Qt 5 to Qt 6 — modernized the entire codebase while preserving all existing functionality and visual rendering
  • GitHub Actions CI/CD — automated multi-platform builds; releases are now published automatically with pre-built binaries for Windows (.zip), Linux (.AppImage), and macOS (.dmg)

New Features

  • Undo / RedoCtrl+Z to undo, Ctrl+Shift+Z (or Ctrl+Y on Windows) to redo any action (add, remove, move, clear)
  • Zoom & PanCtrl+Scroll to zoom in/out (up to 10x), Ctrl+Drag or Middle Mouse Drag to pan, Ctrl+0 to reset
  • Copy / Paste bounding boxesCtrl+C to copy all boxes from the current image, Ctrl+V to paste into another image
  • Move bounding boxes — drag an existing box with Left Click + Drag to reposition it
  • Change label of existing boxAlt+Click (or Option+Click on macOS) to reassign the class of a focused box without redrawing
  • Arrow key nudgingArrow Keys to nudge a box ~1-2px, Shift+Arrow Keys for ~5px steps
  • Usage timer — status bar timer tracks how long you've been labeling (focus-only, pauses when window is unfocused)
  • CLI arguments — launch with ./YoloLabel [dataset dir] [class file] to start labeling directly

Bug Fixes

  • Fixed slider range not updating after image deletion
  • Fixed multiple crash and correctness issues from code review
  • Fixed large image loading failure (removed allocation limit)
  • Fixed undo state not saving on label change
  • Fixed arrow key nudge: undo without target, box escaping cursor on hold, cursor flicker after drag
  • Reassigned "clear all boxes" shortcut from Ctrl+C to Ctrl+Delete to avoid conflict with copy
  • Fixed second click not working when mouse is outside image boundary (#53)

Contributors

Huge thanks to everyone who contributed to this release! 🎉

  • @vusallyv — Undo/Redo, Copy/Paste annotations, Move boxes by dragging, Change label of existing box, Arrow key nudging, Zoom & Pan
  • @pipothebit — CLI argument support for launching with dataset directory and class file
  • @euilee0129 — README improvements

Downloads

OS File
Windows (x64) YoloLabel-Windows-x64.zip — Unzip and run YoloLabel.exe
Linux (x64) YoloLabel-Linux-x64.AppImagechmod +x and run
macOS YoloLabel-macOS.dmg

macOS note: The macOS binary is not signed with an Apple Developer certificate. macOS Gatekeeper will block it from running. To use YoloLabel on macOS, please build from source (requires Qt 6). See the README for instructions.

v1.2.1

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@developer0hye developer0hye released this 13 Jan 03:20

Important Updates

  • Minor bug fix related to the visualization of class name function
  • Release Ubuntu 22.04 version #19

v1.2.0

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@developer0hye developer0hye released this 10 Jan 13:30
78fb3a5

Important Updates

@e8035669 implemented the class name visualization function. It is related to #43.

Thank @e8035669!

Users can turn on or off this function with checkbox or shortcut v.

image

image

v1.1.1

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@developer0hye developer0hye released this 28 Nov 04:46
63bd34f

Acknowledgements

I wish to thank to AIM for supporting me to update and release this version.

Important Updates

  • Removed Unnecessary Buttons that can be replaced by shortcut.

image

  • Added image contrast control function

cut (2)

v1.0.0

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@developer0hye developer0hye released this 25 Nov 15:20

First release on github!