无法在Google Cloud Vision对象检测中开始训练，训练测试验证未拆分 [英] Can't start training in Google Cloud Vision Object Detection, Train Test Validation not splitting

问题描述

我在开始在Google Cloud Vision上训练对象检测模型时遇到问题.我上传了342张4类图片，并标记了102张图片.每个类别有38、24、20、20个标记图像，其中一些图像具有多个边界框.在标签统计信息"窗格中，它说每个标签应至少具有10个边界框，每个边界框至少应具有8、1、1个边界框.它还写道:您的数据集将自动分为训练，验证和测试集."但是我所有的标签都留在Train列中，而val和test列为零.还有其他方法可以手动拆分它们，还是我错过了要点?

I am having problem in start training Object Detection model on Google Cloud Vision. I have uploaded 342 images of 4 classes, and labelled 102 of them. There are 38,24,20,20 labelled images for each class some of which have multiple bounding boxes. In the Label Stats pane, it says each label should have at least 10 bounding boxes, and at least 8, 1, 1 bounding boxes each. It also writes "Your dataset will be automatically split into Train, Validation, and Test sets." But all my labels stay in Train column and val and test columns are zero. Is there any other way to split them manually, or am I missing a point?

推荐答案

您可以创建一个CSV文件，其中包含图像URI和标签，其中包括图像所属的集合(例如，TRAIN，VALIDATION或TEST).参考

You can create a CSV file containing the image URI and labels including to which set (e.g. TRAIN, VALIDATION or TEST) does the image belongs to. Reference

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