mAP scores on tensorboard (Tensorflow Object Detection API) are all 0 even though the loss value is low
I recommend several checks to make sure you get reasonable mAP@IoU scores for object detection API:


Try varying the Intersection over Union (IoU) threshold, e.g 0.2-0.5 and see if you get an increase in average precision. You would have to modify matching_iou_threshold parameter in object_detection/utils/object_detection_evaluation.py
Try different evaluator classes (the default one is EVAL_DEFAULT_METRIC = 'pascal_voc_detection_metrics'). If you are training on Open Image Dataset it makes sense to use open_images_V2_detection_metrics
Check your eval config file and increase the number of examples used in the evaluation set, e.g.

eval_config: {
  num_examples: 20000
  num_visualizations: 16
  min_score_threshold: 0.2
  # Note: The below line limits the evaluation process to 10 evaluations.
  # Remove the below line to evaluate indefinitely.
  max_evals: 1
}
Train the object detector for more iterations
Check current mAP against reported metrics (e.g. COCO mAP@IoU=0.5):