buxihuo / ow-yolo Goto Github PK
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Detect known and unknown objects in the open world(具有区分已知与未知能力的全新检测器))
没有发现哪里有做开集识别的地方。。。
我导入了yolo v5的loss.py,直接训练模型,但是找不到未知标签。
感谢up分享学习案例!
作者您好,utils文件夹中好像缺少了loss函数。
没有推理文件嘛
(不是催更)
I've seen many open-set object detection projects that can detect "seen unknowns" (classes that are already present, although unlabeled, in the training pipeline).
But I'm looking to detect "unseen unknowns" (classes that do not exist in the image space of the dataset at all). Is this project capable of doing this, at least to certain capability?
这里什么也没有
Hello, thanks for your work! It is interesting! And will there be any related papers to be released?
Incremental learning 应该是Open Wold问题中的一个子模块,想知道作者是如何进行增量学习的
兄弟,论文发表了吗,可以上传一下损失函数吗,或者私发我也行[email protected],谢谢(我不做通用领域的,不用目标检测开放数据集,和你的论文没有冲突)
你好我想问一下,添加未知类分数训练模型区分已知未知时,是否有负样本的参与,即手动标注的未知对象。如果没有又是如何训练模型在已知类上的未知分数趋近于0。
使用您提供的预训练权重预测会出现
IndexError: list index out of range
请问:
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