yolov4-pytorch
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各位大佬！请问如果计算[email protected]:0.95呢？项目中get_map.py计算出来的是[email protected]吧？非常感谢

Open zhangmingjiang1114 opened this issue 4 years ago • 7 comments

Aug 29 '21 15:08 zhangmingjiang1114

可不可以将get_map.py中的MINOVERLAP = 0.5，分别修改从0.5到0.95（间隔0.05），计算10次后，求平均值

Aug 29 '21 16:08 zhangmingjiang1114

你可以这么做，我最新上传的yolox里面倒是有代码

Sep 07 '21 14:09 bubbliiiing

你可以这么做，我最新上传的yolox里面倒是有代码

谢谢！

Sep 17 '21 13:09 zhangmingjiang1114

嗯

Sep 19 '21 16:09 bubbliiiing

你可以这么做，我最新上传的yolox里面倒是有代码请问大佬，输出的结果是这样的，该用那个指标计算MAP0.5-0.95呢？

Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.438 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.666 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.452 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.084 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.294 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.494 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.072 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.397 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.502 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.182 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.360 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.529

Jul 24 '24 02:07 guiguiguiguigui

可不可以将get_map.py中的MINOVERLAP = 0.5，分别修改从0.5到0.95（间隔0.05），计算10次后，求平均值

请问大佬，输出的结果是这样的，该用那个指标计算MAP0.5-0.95呢？

Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.438 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.666 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.452 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.084 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.294 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.494 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.072 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.397 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.502 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.182 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.360 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.529

Jul 24 '24 02:07 guiguiguiguigui

请问大佬们，输出的结果是这样的，该用那个指标计算MAP0.5-0.95呢？

Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.438 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.666 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.452 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.084 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.294 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.494 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.072 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.397 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.502 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.182 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.360 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.529

Jul 24 '24 02:07 guiguiguiguigui