Comments (2)
我用作者保存的训练好的ddrnet23-slim, 跑了cityscapes测试集,上传到官网,得到的结果是76.38, 而不是77.44, 是我漏掉了什么设置吗?有挺多模型都是这样得不到论文中的精度。
我提供的模型是只在训练集上训练的模型,对应于在评估集上的结果。在测试集测试的模型一般都用训练集加评估集的数据一起训练,会有一定的涨点。我觉得可能是这个原因。
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我用作者保存的训练好的ddrnet23-slim, 跑了cityscapes测试集,上传到官网,得到的结果是76.38, 而不是77.44, 是我漏掉了什么设置吗?有挺多模型都是这样得不到论文中的精度。
我提供的模型是只在训练集上训练的模型,对应于在评估集上的结果。在测试集测试的模型一般都用训练集加评估集的数据一起训练,会有一定的涨点。我觉得可能是这个原因。
哈哈,好吧,那我也试试看。
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Related Issues (20)
- 您好,想請問會公開訓練的code嗎? HOT 1
- DAPPM + DDRNet slim for small image segmentation input_size (e.g. 128x128 or 256x256) HOT 1
- Not an issue, but applause! HOT 1
- pre-trained model on the COCO dataset HOT 1
- Error in code or paper? HOT 1
- About camvid HOT 3
- Saved model without pretraining HOT 2
- About the structure of the DDRNet HOT 1
- where is the 'Bottleneck_last' and 'SPP_super' in ddrnet.py
- 关于图片尺寸 HOT 1
- 可否上传ImageNet预训练的代码 HOT 1
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- 有关训练的问题 HOT 3
- Train model problem
- 关于辅助损失 HOT 1
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- 关于2080ti的推理速度 HOT 1
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