Visualizing Object Detection Data in TensorFlow with TFRecords

This tutorial demonstrates how to visualize object detection datasets in TensorFlow using TFRecords, decode ground-truth labels, and overlay bounding boxes and masks for better model insight. It concludes with evaluating model performance using mean Average Precision (mAP), following COCO standards, and offers tips on debugging visualization and training logs for accurate detection results.