[英]Best strategy for Object localisation without using pretrained model and weights.?
我想从头开始训练模型,而无需使用任何预先训练的模型和权重以及20k图像数据集和4个对象坐标。您能建议我解决此问题的最佳方法吗?
Why won't you try any of the existing architectures - YOLO, SSD, Faster-RCNN to name a few (or their next-gens) and see what is the performance? 您为什么不尝试任何现有架构-YOLO,SSD,Faster-RCNN等(或它们的下一代),看看它们的性能如何?
Of course, if you know in advance the properties of the objects in your data set this can be useful - eg for smaller objects, Faster-RCNN would probably yield better performance that SSD and YOLO. 当然,如果您事先知道数据集中对象的属性,这将很有用-例如,对于较小的对象,Faster-RCNN可能会产生比SSD和YOLO更好的性能。
Each one of them has available open source implementations in all leading DNN frameworks. 他们每个人在所有领先的DNN框架中都有可用的开源实现。
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