Comments (4)
Thanks, we have updated the README!
from up-detr.
Thanks for your attention. you need to add --pre_norm
.
In our experiments, we use --pre_norm
by default.
There are some papers (in NLP) noting that --pre_norm
is a little better, so we use it in all of our experiments (including our reimplemented counterpart).
Feeling free to this setting, it does not affect too much performance of DETR.
from up-detr.
read more: facebookresearch/detr#93
Because of the paper: https://arxiv.org/abs/2002.04745, so we adopt --pre_norm
in our early experiments.
from up-detr.
It works, thank you! Probably adding the full eval bash line to README would be a worthy thing.
from up-detr.
Related Issues (20)
- Error in notebook while loading up-detr-coco-fine-tuned-300ep.pth HOT 2
- Some questions about your code HOT 5
- Questions about the multi-query patch model HOT 1
- bounding boxes shift problem
- How extract precision, recall and f1-score metrics HOT 1
- Code for VOC HOT 2
- detectiong objects HOT 1
- Class Loss HOT 2
- SWAV HOT 1
- Random Crop HOT 2
- num_classes HOT 6
- How to support batch learning for one-shot object detection training? HOT 8
- Getting access to the one-shot object detection training code
- 请问如何在coco上预训练?
- backbone的build时会构建position embeding,需要用到nestedtensor的mask,请问输入tensor类型的patch不会报错吗
- 请问是否可以开源one-shot部分的训练代码
- Unexpected key(s) in state_dict: "feature_align.layers.0.weight", "feature_align.layers.0.bias", "feature_align.layers.1.weight", "feature_align.layers.1.bias", "patch2query.weight", "patch2query.bias". HOT 1
- 请问微调300个epoch能收敛吗?为什么我在自己数据集微调了600个批次都收敛不了 HOT 1
- _IncompatibleKeys HOT 1
- Evaluation problem
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