Comments (1)
Hi Alex,
Thanks for your interest in the AI-TOD series. I think this observation is interesting, and we haven't noticed it yet. Given that the original version of this dataset has been used in the community for benchmarking algorithms for more than two years, it is hard to make adjustments to it and filter out overlapping parts if they do exist.
In this case, I recommend using v2 since the number of overlapping boxes takes up a small portion of the whole dataset. Besides, as long as the method was evaluated under the same experimental setting, I think this dataset is still a good candidate for benchmarking tiny object detection since the sota mAP is still extremely low. Moreover, you can filter out these overlapping boxes and get a high-quality dataset if you would like to.
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Related Issues (20)
- How to download Xview Training set in terminal? HOT 1
- What is the keyword of AI-TOD_wo_xview HOT 1
- ModuleNotFoundError: No module named 'lxml' HOT 1
- 请问aitod(不包括xview部分)是coco格式吗? HOT 1
- Not able to find the xview_train.geojson file HOT 3
- Error in tiff images while executing python generate_aitod_imgs.py. HOT 21
- Is there any other way to download the AITOD dataset, such as Baidu Netdisk ? HOT 9
- AI-TOD的标签 HOT 2
- AP未达到论文中报告的结果 HOT 4
- NameError: name 'wasserstein_nms' is not defined HOT 1
- 如何支持其他框架的aitod数据集适配 HOT 1
- Python tool generate_aitod_imgs.py doesn't generate a combined AI-TOD and xView dataset with JSON annotations for use in MMDET-AITOD training HOT 11
- 是否有合并之前的ai-tod的annotations?
- Clarification Needed on Bounding Box Coordinate Conversion for AI-TOD Dataset in YOLO Format HOT 1
- 请问AI-TOD数据集怎么转换成YOLO格式
- Emergency!!!Error using AI-TOD dataset HOT 4
- A Guide on Generating AI-TOD问题 HOT 3
- test.py推理图片请教,谢谢 HOT 1
- 没看到模型初始化权重
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