I am training some Object-Detection-Models from the TensorFlow Object Detection API and got from the evaluation with MS COCO metrics the following results for Average Precision:
IoU = 0.5;0.9 maxDets = 100 area = small AP = -1.000
The other values all make sense to me. But I don´t know what the -1.000 stands for. Does it mean that there are no small objects in my dataset to be detected?
APsmall stands for Average Precision for small objects.
This website contains all the descriptions about the metrics: https://cocodataset.org/#detection-eval
If you want to know more about the metrics evaluation (how to calculate this metric), you can find the metric's source code here: https://github.com/cocodataset/cocoapi/blob/master/PythonAPI/pycocotools/cocoeval.py
Does it mean that there are no small objects in my dataset to be detected?
Yes.
From the evaluation source code as mentioned by the other answer, L334:
-1 for the precision of absent categories
From the coco dataset website, Detection Evaluation:
$AP_{small}$: AP for small objects: area < $32^{2}$
$AP_{medium}$: AP for medium objects: $32^{2}$ < area < $96^{2}$
$AP_{large}$: AP for large objects: area > $96^{2}$
