Comments (10)
SpursLipu
commented on June 8, 2024
这个是数据集的问题，dior主要是卫星遥感图片，你可以试试用visdrone训练出的权重文件。
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pch9520
commented on June 8, 2024
我用visdrone的权重也试过，不行的。对于Dior训练出来的权重，我把Dior数据集中的卫星遥感图片喂进去测试出来效果也是很差的，都检测到frisbee去了，没有检测出车辆
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SpursLipu
commented on June 8, 2024
你看看imgsize对不对我训练的都是应该用的都是608的。
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SpursLipu
commented on June 8, 2024
我md上放的就是dior测试集的图片，权重应该没问题，你看看你的设置
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pch9520
commented on June 8, 2024
我是下载了你的.weights文件以后在darknet上测试的，识别不了，是不是转换成.weights文件的过程中出错了
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SpursLipu
commented on June 8, 2024
转化应该没有问题...在我的仓库是可以测试的，你用了我的cfg文件了吗？
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SpursLipu
commented on June 8, 2024
yolov3.cfg与我仓库里面使用的yolov3-visdrone.cfg文件是不同的，类别设置，anchor不一样
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pch9520
commented on June 8, 2024
好的，我了解了，我明天试试，dior的weights对应yolov3-onDIOR.cfg，visdrone的weights对应yolov3-visdrone.cfg对嘛？
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pch9520
commented on June 8, 2024
我试了一下，可以用了，但是在我们自己的视频上检测率不是很高，我们应该还要继续训练
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SpursLipu
commented on June 8, 2024
如果是你们自己的数据集，还是再训练下比较好
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Related Issues (20)
- normal裁剪模型后的微调报错shape'[52,29,3,3]' is invalid for input of size 13382
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- NameError: name 'Darknet' is not defined HOT 1
- AttributeError: module 'torch.distributed' has no attribute 'init_process_group' HOT 2
- 自己跑的VisDrone数据和你相差过大 HOT 2
- Question in the inference ?
- RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! HOT 3
- RuntimeError: size mismatch, m1: [8 x 1], m2: [8 x 1] at /pytorch/aten/src/THC/generic/THCTensorMathBlas.cu:283
- Compatibility with yolov4-tiny
- conv_b = torch.from_numpy(weights[ptr:ptr + num_b]).view_as(conv_layer.bias) RuntimeError: shape '[18]' is invalid for input of size 0 HOT 1
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- Is there a way to convert the best.pt model with -quantized 1 to .onnx?
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- train.py 437行，为什么最终的loss要乘batch_size / 64?( loss *= batch_size / 64 # scale loss)
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