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Zzh-tju / CIoU

Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression (AAAI 2020)
GNU General Public License v3.0
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test_dev 上的evaluation 执行python eval.py --trained_model=weights/yolact_base_54_800000.pth --output_coco_json --dataset=coco2017_testdev_dataset命令后 生成bbox和mask两个json文件，而非一个json文件 #22

Closed Slonna closed 1 year ago

Slonna commented 1 year ago

我该怎么做才能获得单个的json文件，用于coco服务器提交评测

Slonna commented 1 year ago

生成的两个bbox.json ,mask.json 可分别重命名后进行提交，获得相应分数