Pehra Gemma 4 PPE Evaluation Data: Images and Model Predictions

The dataset contains images of Personal Protective Equipment (PPE), corresponding ground truth annotations, and predictions generated by the Gemma 4 E4B model. It appears to be designed for evaluating the performance of the Pehra model or similar computer vision systems on PPE detection tasks. The author, organization, and specific data volume are unknown.

Use Cases

• Benchmarking PPE detection models based on provided ground truth annotations.
• Evaluating the prediction accuracy of the Gemma 4 E4B model on PPE images.
• Training or fine-tuning object detection models for safety compliance using the image collection.
• Analyzing failure cases in PPE recognition by comparing ground truth and model predictions.

Strengths

• Includes ground truth annotations, which are essential for model evaluation.
• Provides predictions from a specific, named model (Gemma 4 E4B) for direct comparison.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Collection Method

Likely contains images and annotations gathered for evaluating a PPE detection model.