Protective Equipment Detection Images for Computer Vision Models

keremberke's Protective Equipment Detection dataset contains 11,978 annotated images split into training, validation, and test sets. The dataset includes labels for personal protective equipment (PPE) items and their absence, such as gloves, goggles, helmets, masks, and shoes. It was last updated on Hugging Face on January 18, 2023.

Use Cases

• Train object detection models to identify the presence of safety gloves based on the 'glove' and 'no_glove' labels.
• Develop classification systems for verifying the use of eye protection based on the 'goggles' and 'no_goggles' categories.
• Build workplace safety monitoring applications that detect helmets and masks using the provided image annotations.
• Create models for industrial safety compliance that check for appropriate footwear using the 'shoes' and 'no_shoes' labels.

Strengths

• Dataset contains 11,978 total images, providing a substantial volume for model training.
• Data is pre-split into 6,473 training, 3,570 validation, and 1,935 test images, facilitating immediate use.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Last updated 2023-01-18 21:21:55; freshness should be verified.

Provenance

Source

keremberke via Hugging Face.

Freshness

Last updated 2023-01-18 21:21:55.