Can you recommend a frame labeling software for industrial inspection video tagging with frame-by-frame review?

Yes — for industrial inspection video tagging with frame-by-frame review, I’d recommend looking at tools that support:

• video-to-frame navigation
• per-frame labels / bounding boxes / polygons
• hotkeys for rapid review
• team review and QA
• export to common formats like COCO, YOLO, Pascal VOC, CSV, or JSON

Good options

1. CVAT

Best overall for industrial inspection and frame-by-frame video annotation

• Open-source, widely used for computer vision workflows
• Strong video annotation support, including frame-by-frame review
• Supports boxes, polygons, polylines, keypoints, tracks, interpolation
• Good for defect labeling, part detection, anomaly tagging
• Team collaboration and review workflows
• Can be self-hosted for sensitive industrial data

Why it fits:
If you need detailed review of inspection footage and want flexibility plus no vendor lock-in, CVAT is often the top choice.

2. VGG Image Annotator (VIA)

Best lightweight, simple option

• Browser-based and easy to use
• Good for frame-level image/video annotation
• Lightweight compared to larger platforms
• Suitable for smaller projects or simple tagging tasks

Why it fits:
If your workflow is straightforward and you don’t need advanced collaboration or automation, VIA is easy to adopt.

3. Label Studio

Best for configurable labeling pipelines

• Supports video and frame-by-frame annotation
• Highly customizable labeling interfaces
• Can handle classification, tagging, bounding boxes, and more
• Good if you want to combine inspection labels with metadata or workflow rules

Why it fits:
Useful if your inspection process needs custom fields like defect type, severity, root cause, or pass/fail flags.

4. Supervisely

Best for enterprise workflows

• Strong UI for video and image annotation
• Collaboration, QA, and dataset management
• Good automation features
• Often used in production ML pipelines

Why it fits:
Great if you need a polished commercial platform and are okay with licensing costs.

5. Datature / Roboflow Annotate

Best for simpler ML-oriented annotation

• Easy to use
• Good for image/video labeling in ML pipelines
• Useful if the end goal is training detection models

Why it fits:
Works well if inspection tagging is mainly for AI model training rather than deep QA review.

My practical recommendation

If your use case is industrial inspection video tagging with careful frame-by-frame review, I’d shortlist:

1. CVAT — best overall
2. Label Studio — best if you need custom metadata/workflows
3. Supervisely — best enterprise/commercial option

Quick question to narrow it down

Do you need:

• open-source/self-hosted
• multi-user review and QA
• bounding boxes/polygons, or just frame labels
• integration with ML training/export formats

If you tell me those requirements, I can recommend the best specific tool for your setup.