Video Training Data for Manufacturing Process Understanding

It is the labeling of recorded production footage for tasks such as assembly-step recognition, component tracking, and machine-state understanding. Unitlab connects annotations to video frames and review workflows.

Define the process states in the ontology and record their changes over the relevant frames. Review ambiguous transitions against the original footage and the agreed start/end convention.

Yes. Create a persistent object track, refine its geometry with keyframes, and inspect visibility changes. Assisted tracking or interpolation can support the work where available, with human review of the result.

Use observable actions and defined relationships, such as a person handling a component or using a tool. The dataset guidelines should state the visual evidence needed for each label.

Process-video annotation labels what the camera records across frames. Sensor annotation labels time ranges and points in numeric measurements such as vibration, temperature, or pressure.

Define shared classes, structured properties, and clear labeling instructions before work starts. Use representative examples and contextual review to resolve disagreements in the manufacturing process understanding dataset.

Yes. Route video annotation through Review and Rework stages. Reviewers can inspect the source data, correct labels, and send an item back when more work is needed.

Yes. Use dataset search, metadata, tags, and available filters to select relevant video assets. Keep representative conditions and difficult examples visible in the preparation workflow.

Export reviewed video annotations in a supported format appropriate to the label types. Dataset versions help teams identify which prepared examples belong to the training or evaluation release.