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After the training is completed by train_net.py, the terminal prints the verification results on COCO_val. I understand that according to the self-supervised process, you should fix the self-supervised training part of the backbone network, then fine-tune the detection head on the labeled data, and then go to COCO_val to evaluate the performance. But I don't see where InsLoc is fine-tuned training, where is this step achieved? Hope to get your answer
After the training is completed by train_net.py, the terminal prints the verification results on COCO_val. I understand that according to the self-supervised process, you should fix the self-supervised training part of the backbone network, then fine-tune the detection head on the labeled data, and then go to COCO_val to evaluate the performance. But I don't see where InsLoc is fine-tuned training, where is this step achieved? Hope to get your answer
通过train_net.py训练完成后,终端打印了在COCO_val上的验证结果。我理解按照自监督的流程,应该固定自监督训练得到的主干网络部分,然后在有标签数据上微调检测头后,再去COCO_val上评估性能。但我没看到InsLoc是在哪里进行微调训练的,请问这一步是在哪里实现的呢?希望得到您的解答
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