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zhangxuying1004 avatar zhangxuying1004 commented on May 25, 2024

非常感谢你能开源论文的代码。但是在 evaluation 中,并没有计算 spice 分数的相关代码,我想知道你是如何得到 spice 分数的?

您好,这里把spice部分去掉的原因是训练过程中计算spice太耗时,模型训练好以后,测试时加上即可。把https://github.com/ruotianluo/coco-caption/tree/ea20010419a955fed9882f9dcc53f2dc1ac65092/pycocoevalcap 这个链接下的spice文件夹放到evaluation文件夹下,并在__init__.py中把spice引入即可。

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amazingYX avatar amazingYX commented on May 25, 2024

非常感谢你能开源论文的代码。但是在 evaluation 中,并没有计算 spice 分数的相关代码,我想知道你是如何得到 spice 分数的?

您好,这里把spice部分去掉的原因是训练过程中计算spice太耗时,模型训练好以后,测试时加上即可。把https://github.com/ruotianluo/coco-caption/tree/ea20010419a955fed9882f9dcc53f2dc1ac65092/pycocoevalcap 这个链接下的spice文件夹放到evaluation文件夹下,并在__init__.py中把spice引入即可。

非常感谢,这对我帮助很大!

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amazingYX avatar amazingYX commented on May 25, 2024

你好,非常抱歉,再次打扰你。我对于 beamsearch.py 中对 visual 进行 expand 的操作不是很理解,visual 只是当 t=0 时,作为 encoder 的输入,得到 self.enc_output,decoder 的输入也只有 self.enc_output。对 self.enc_output 进行 expand 后,visual 感觉就没有必要再进行处理了,为什么要多此一举?

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