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高堡奇人

UGATIT 预训练模型和数据集百度云下载，为方便谷歌硬盘无法使用的人，不懂的可加Q群857449786 注明UGATIT 共同研究，谢谢！官方已经开放的数据集和模型在google硬盘，比较大，可能无法下载，我分卷压缩了一下，分享到百度云，方便大家下载。

Light is set to False, and if it is set to ture, the model must be retrained, and the default model cannot be imported. The default model is set to...

UGATIT 预训练模型和数据集百度云下载，为方便谷歌硬盘无法使用的人，不懂的可加Q群857449786 注明UGATIT 共同研究，谢谢！官方已经开放的数据集和模型在google硬盘，比较大，可能无法下载，我分卷压缩了一下，分享到百度云，方便大家下载。

> 模型解压不了啊 checkpoint有问题官方只放出了tensorflow版本的预训练模型。没有pytorch版本的预训练模型

UGATIT 预训练模型和数据集百度云下载，为方便谷歌硬盘无法使用的人，不懂的可加Q群857449786 注明UGATIT 共同研究，谢谢！官方已经开放的数据集和模型在google硬盘，比较大，可能无法下载，我分卷压缩了一下，分享到百度云，方便大家下载。

light 设置为 False，如果设置为ture，必须重新训练模型，默认模型无法导入。默认模型是设置为 False的7.5G，如果是设置为ture，模型只有1G，你们看看自己的设置。也可以把官方的tf模型转换为pytorch模型。

CornerNet has recently been upgraded to CornerNet-Lite, and has made great progress. Do you have a comparison of the efficiency and time of testing with CornerNet's AP detection?

**Can you help me add the parameters of CenterNet to the model files CornerNet_Saccade.py and CornerNet_Squeeze.py?Thank you very much! Because the format of CornerNet-Lite's training model file has changed, and...

CornerNet has recently been upgraded to CornerNet-Lite, and has made great progress. Do you have a comparison of the efficiency and time of testing with CornerNet's AP detection?

> Sorry, we have not yet. **Can you help me add the parameters of CenterNet to the model files CornerNet_Saccade.py and CornerNet_Squeeze.py?Thank you very much! Because the format of CornerNet-Lite's...

CornerNet has recently been upgraded to CornerNet-Lite, and has made great progress. Do you have a comparison of the efficiency and time of testing with CornerNet's AP detection?

WIN10下已经解决了安装和训练，还有问题的，可以加Q群264191384 注明（CenterNet）共同研究，谢谢

高堡奇人

CornerNet has recently been upgraded to CornerNet-Lite, and has made great progress. Do you have a comparison of the efficiency and time of testing with CornerNet's AP detection?

CornerNet has recently been upgraded to CornerNet-Lite, and has made great progress. Do you have a comparison of the efficiency and time of testing with CornerNet's AP detection?

CornerNet has recently been upgraded to CornerNet-Lite, and has made great progress. Do you have a comparison of the efficiency and time of testing with CornerNet's AP detection?

尝试在win 10 上运行 demo.py

Failed to get convolution algorithm.

Failed to get convolution algorithm.

已经解决了win10下关于faster rcnn下训练自己数据集的问题，如有不了解的，可以交流