Comments (3)
VYXUOF
commented on June 12, 2024
我是使用的你提供的yolov4tiny来训练的 得出的模型很小 目前训练出了一个map4.8的模型 检测方面已经可以检测出来一点点东西了 但是目前训练速度太慢了 我调整了batch、epoch、learn rate等参数，但始终无法将训练速度和mAP值上升速度加快
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yuto3o
commented on June 12, 2024
tensorflow训练tiny版本网络时GPU占用就是比较低，我还没有找到比较好的办法。训练正常大小的yolo模型GPU占用倒是正常。应该是模型本身的问题，或者是训练模型的解码过程比较占用GPU时间；
learning rate 可以先不管，默认的learning rate已经比较通用，可以尝试适当减小epoch的数量；或者在进行在线验证时，减小验证集的大小，也可以进一步加快训练过程；还不行的话，请不要先使用任何的数据增强手段，训练试试。请保持代码与本仓库的训练一致，因为我的代码在一边训练，一边微调，可能之前的某些参数设置会影响训练效果。
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VYXUOF
commented on June 12, 2024
好的 谢谢大佬 我这边继续尝试调参
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Related Issues (19)
- Getting Error while executing yolo_utils.non_max_suppression(predictions) HOT 1
- AP is not improved!!! HOT 1
- yolox initial weight HOT 3
- conv2d_17_loss 和conv2d_20_loss HOT 1
- convert weights to .h5 HOT 2
- IndexError: index 3 is out of bounds for axis 0 with size 3 HOT 5
- Reason for calling fit thrice in train.py HOT 4
- GPU usage HOT 1
- backbone yolov4 HOT 3
- Handling non-square images HOT 2
- Does your code support all the functions of yolov4 and can it train normally ? HOT 3
- where do I find ./ckpts/yolov4.weights
- yolov4-tiny pretrained model? HOT 1
- train.py not working HOT 4
- train error!!!!! HOT 2
- 通过关闭cfg中的数据增强手段和减小epch大小 确实加快了训练速度 但map值却一直没有上涨 HOT 3
- Transform Model to Real_Time: Serialize Model HOT 1
- Weights file used in the implementation HOT 7
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