Problem and data
Define classes, object size, scene variation and the resulting decision. Images need permitted use and consistent labelling. Split training, validation and test sets; near-identical frames from one scene must not leak across them.
Development and integration
Model family, implementation and licence are assessed for each YOLO project. Training and optimisation are followed by camera input, inference, thresholds and application interfaces. A model name alone does not establish hardware compatibility or commercial licence rights.
Evaluation and deployment
Review precision, recall, per-class errors and application latency together. Validate on independent test data; desktop trials are not presented as field performance. After edge deployment, preprocessing and result consistency are checked again.