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Some questions about the image features #21
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You could modify the option "model. img_feature_size" in the file "rva/configs/rva.yml" from 2048 to 1024. |
感谢你的回复,但我还是想问下,为什么detectron提取出来的是1024,但模型使用的都是2048,这个是如何变化的呢?如果将文件中的 "model. img_feature_size" 改为1024会对结果有什么影响吗?因为我是在想利用以前的提取特征方法,将自己的数据集重新提取特征,跟原来batra-mlp-lab提取的特征保持一致,然后夹杂着一起使用,我看大家都是用的detectron来提取的特征,但我在使用时发现提取的特征是(36,1024)的,如果我直接利用全连接层将这个特征的shape改成(36,2048),然后放入到原来提取好的特征中,我怕这样会对我的结果产生影响。 |
请问你用的哪一个detectron的模型?根据batra-mlp-lab的代码https://github.com/batra-mlp-lab/visdial-challenge-starter-pytorch/blob/master/data/extract_features_detectron.py,提取特征的模型是基于faster_rcnn_x101的,你可以选取对应的模型提取自己的特征 |
是的,我就是选择的他所说的模型,但是特征shape不对应,不太理解。 |
Hello, i want to ask about the image features which are extracted from the detectron. When i extract them, i find their shapes are (36,1024), but the features' shapes which are extracted by batra-mlp-lab are (36,2048). So my question is how to deal with this problem? Thanks.
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