LabelOp Blog
Computer vision annotation and labeling guides.
Practical guidance on image annotation, data labeling, QA review, dataset formats, versioning, and export for teams building training-ready computer vision data.
1–12 of 71 articles
Export Tracked Video Annotations to COCO and YOLO Training Formats
What each LabelOp Tracker export contains, which format keeps track IDs, how train/val splits work for a single video, and the checks to run before you train.
ReadHow to Find Frames Worth Labeling in Long Videos
Hours of footage, a handful of rare scenes. Use natural-language video search to shortlist candidate timestamps, then label the frames that matter in LabelOp.
ReadLabelOp Tracker: A Free Video Annotation Tool That Runs in Your Browser
Open a video, auto-annotate it on your GPU, fix the tracks and export COCO or YOLO. A step-by-step walkthrough of LabelOp Tracker, plus its limits and requirements.
ReadHow On-Device Video Search Works: Frames, Embeddings and Similarity
A plain look inside LabelOp Moments: how a browser samples a local video, turns frames and text into embeddings, ranks moments, and where the approach falls short.
ReadHow to Prepare Clean Object Images for a Computer Vision Dataset
Reference shots, cutouts for copy-paste augmentation, and classifier crops: how to prepare object images on your own device, what to keep original, and where labeling takes over.
ReadRemove a Photo Background in Your Browser Without Uploading It
A step-by-step guide to removing a photo background locally with LabelOp Retouch: the cutout, edge refinement, new backdrops, export presets, and the limits to know first.
ReadSearch a Video by Describing the Scene: A Guide to LabelOp Moments
LabelOp Moments finds moments in a local MP4 when you describe what is on screen. Here is how it works, what to type, and where it falls short.
ReadUpscale and Denoise Photos in Your Browser with Local AI
How to enlarge a photo 2x or 4x and clean up noise and JPEG artifacts on your own device with LabelOp Retouch, including size limits, a good order of operations, and when not to do it.
ReadHow Many Images Do You Need to Train YOLO?
What Ultralytics actually recommends for images and labeled objects per class, why fine-tuning changes the starting point, and how to count what your dataset already has.
ReadHow to Remap YOLO Class IDs: Merge, Reorder, or Drop
Change the class index in YOLO label files without breaking your dataset. A safe Python script for detection and segmentation labels, plus the data.yaml and cache steps people forget.
ReadFix YOLO data.yaml and Dataset Not Found Errors
Why Ultralytics YOLO cannot find your images or labels, what "label class exceeds nc" means, and how path resolution, folder naming, names, nc, and cache files actually work.
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