OrientedRepPoints
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LiWentomng
数据
I'm learning your code about Oriented RepPoints. But I am a novice，there are many problems in data set preparation,I have just come into contact with this direction, so I am not very clear about the conversion and processing of data formats. Can you send me a complete set of data you have prepared？（as on your web page）
@ziruoliu Hello, the code for DOTA data preparation, please refer this code-prepare_dota1_ms.py to get single-scale image patches. The json format is similar as COCO json with 8 points(ploy) for box annotation as in DOTA2COCO_poly.py.
@LiWentomng Thank you very much for your reply, I have one more question for you. I was reading the paper to see experiments about angular errors. I don't see where it comes from, I wonder how you define it. "mean Average Orientation Error (mAOE◦) "
@ziruoliu Sorry to reply later. mAOE is the diferences of the detection and prediction on angular orientation . The angle definition for orientation can refer this . The codes for mAOE is here and the corresponding line of angle definition is here.
@LiWentomng 你好，还有一个问题想请教一下，dota数据集分割之后，有的图片里面就没有目标，它所对应的标注文件也是空的。那么在训练的时候，这些图片需要剔除掉吗？还是说数据集分割完之后，就不要去管这些问题了。
@runever 你好 不需要自己手动剔除， 本身mmdetection框架下对应的data pipeline 有filter 的操作，过滤掉没有标注的图片，本代码也有过滤掉特别小尺寸的目标的操作。
@LiWentomng 作者您好，我看您在论文中说对于dota数据集“We crop the original images into the patches of 1024 × 1024 with a stride of 824”，但项目文件prepare_dota1_ms.py中gap设置为了824，这样ImgSplit_multi_process.py中的步长slide=subsize-gap岂不是1024-824=200，这个地方不太明白，可能是我理解错了或是gap应该设置成200呢？
