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A question about the evaluation results! #7
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I have the same problem, even when I run the demo.py provided by author. Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets= 20 ] = 0.660 |
same problem. |
same problem, have you guys solved this? @albertter @Z1Wu @FightStone |
evaluation code has bug. |
I have the same problem. Is there any solution? |
self.areaRngLbl = ['all', 'medium', 'large'] And the code tried to get evaluation result when area_range is easy, medium, hard. It is supposed to fail. |
This is my evaluation result :
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets= 20 ] = 0.808
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets= 20 ] = 0.955
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets= 20 ] = 0.870
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 20 ] = 0.850
Average Recall (AR) @[ IoU=0.50 | area= all | maxDets= 20 ] = 0.961
Average Recall (AR) @[ IoU=0.75 | area= all | maxDets= 20 ] = 0.899
Average Precision (AP) @[ IoU=0.50:0.95 | area= easy | maxDets= 20 ] = -1.000
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets= 20 ] = 0.790
Average Precision (AP) @[ IoU=0.50:0.95 | area= hard | maxDets= 20 ] = -1.000
Why is there a -1 value? My prediction result format is the same as the prediction json format you provided. Looking forward for your response, thank you!
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