# How to interpret results from CocoEvaluator

I am using the engine.py stuff which uses CocoEvaluator. I tried to get information about CocoEvaluator and tried to understand the code, but I am not sure how to interpret the figures from the output, nor how they relate to the mAP values which are mentioned in all papers.
If a model performs good, are the average precision and recall values close to 1? And what does -1 mean?

``````IoU metric: bbox
Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.337
Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.391
Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.381
Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.649
Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.326
Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000
Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.048
Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.213
Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.837
Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.680
Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.842
Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000
IoU metric: segm
Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.324
Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.391
Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.387
Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.475
Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.318
Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000
Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.045
Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.201
Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.820
Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.740
Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.822
Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000
``````