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This month’s release focuses on improving video annotation workflows, enhancing SAM2 tracking, and adding finer control for editing. These updates are designed to make annotation more accurate, efficient, and user-friendly for both annotators and reviewers.

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1. Frame-by-Frame Precision in Video Annotation

The video player has been upgraded to ensure frame-level accuracy and a smoother annotation workflow. This update addresses sync issues caused by time-based playback and provides a more reliable environment for video annotation. No more labels drifting off-sync. With frame-accurate playback, annotations stick exactly where they should, which means cleaner training data and fewer noisy samples downstream. Key Improvements:
  • Frame-based rendering powered by a backend streaming API
  • Accurate annotation sync with frames during playback and navigation
  • Next and Previous frame controls for precise navigation
  • Manual frame seeking with exact frame display
  • Smooth playback at correct FPS using sequential frames
  • Error handling with retry support and fallback display
  • Loading indicators to manage network delays

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2. Review Annotations Faster with Timeline Keyframes

Keyframes can now be created, managed, and reviewed directly on the video timeline. This makes it easier for annotators to label efficiently and for reviewers to validate annotation quality at a glance. Key Improvements:
  • Visual pins displayed on the timeline for all keyframes in the active track or layer
  • Hover tooltips showing timestamp and frame number for each keyframe
  • Click on any pin to instantly jump the player to that frame
  • Add keyframes using a dedicated button, context menu, or keyboard shortcut (K)
  • Delete keyframes with the Delete key or context menu options
  • Popover list provided for overlapping pins to ensure precise selection
  • Full API integration for fetching, creating, and deleting keyframes with smooth UI updates
  • Keyboard accessibility support with focusable pins and shortcuts
  • Optimized rendering for hundreds or thousands of pins without lag
This update reduces cognitive overhead by providing a faster way to navigate annotations and ensures reviewers can easily assess annotation completeness and accuracy.

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3. Track Multiple Objects in One SAM2 Run

Instead of running SAM2 separately for each object, you can now track all selected annotations in a single job. This dramatically speeds up labeling while lowering compute costs. Key Improvements:
  • Magic wand beside Objects to select timelines that contain SAM prompts
  • Single job execution for all chosen timelines in one run
  • In-app and email notifications on completion or failure
  • Job detail view with status and progress information
  • Option to cancel an active job
  • Option to keep or discard partial progress, with discard as the default
  • Test coverage for backend and UI flows

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4. Apply SAM2 Reliably to Bounding Box Workflows

We resolved errors that appeared during SAM2 runs on bounding box annotations, ensuring a stable and predictable experience for annotators. With this fix, users can confidently create bounding box labels and run SAM2 without interruptions. Key Improvements:
  • Stability fixes for SAM2 execution on bounding box annotations
  • Error-free integration between bounding box labeling and SAM2 tracking
  • More reliable experience when creating projects from new datasets
  • Tested and validated in QA environment with consistent results
This enhancement makes bounding box workflows smoother and ensures SAM2 can be applied seamlessly during annotation.

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5. Enhance Visibility During Annotation with Non-Destructive Filters

Brightness and contrast filters are now built into the labeling interface, helping annotators see details more clearly without altering the source data. This is especially useful for low-light, medical, or noisy datasets. Key Improvements:
  • Reliable controls for brightness and contrast across images and video frames
  • Non-destructive adjustments that preserve the source asset
  • Per-frame and continuous playback rendering with consistent results
  • Reset to default and quick compare to view changes instantly
  • Persistent settings during a session for smoother multi-frame work
  • Keyboard support for fine-step adjustments
  • Clear tooltips and accessible labels for each control
  • Performance tuning for smooth scrubbing and playback while filters are active

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How These Updates Help You

  • Higher Accuracy: Frame-based video playback keeps annotations in perfect sync
  • Faster Workflows: Single SAM2 runs save time and resources
  • Better Visibility: Keyframes, markers, and filters improve clarity
  • Smarter Reviews: Reviewers can quickly validate annotation quality with fewer clicks

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What’s Next

We are preparing additional features such as advanced file management, extended automation support, and improved object detection agents.

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Wrapping Up

The August 2025 release delivers precise frame rendering, smarter SAM2 tracking, intuitive keyframe management, stable bounding box workflows, and improved annotation filters. These updates create a faster, more reliable, and more productive annotation environment. We encourage you to explore the new features and share your feedback with us. Labellerr Team