Comments (3)
可以看一下你的SRvedai.yaml的配置文件吗?
建议从几个方面去确认
1.下载最新的code
2.确保 test.py 使用的是 from utils.datasets import create_dataloader_sr 中的 create_dataloader_sr函数
3.删除cache缓存文件,单步调试到 https://github.com/icey-zhang/SuperYOLO/blob/main/utils/datasets.py 第684行 确认self.img_files路径是否正确
4.我这生成的cache文件是label.cache
5.因为我这这个代码按照这个步骤修改是可以跑起来的,不确定你是哪的问题,所以建议单步调试看看
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非常感谢您迅速的回复!我的SRvedai.yaml的配置文件修改了这三行
train: F:/BaiduNetdiskDownload/dataset/VEDAI/fold01_write.txt
test: F:/BaiduNetdiskDownload/dataset/VEDAI/fold01test_write.txt
val: F:/BaiduNetdiskDownload/dataset/VEDAI/fold01test_write.txt
通过您建议中的方法3我定位到了数据集读取问题出在img2label_paths函数中,我是在windows系统上测试的,而os.sep代表的分隔符和linux不同,将os.sep修改为'/'可以正确读取到文件了。
此外,最新代码的common.py中我发现Conv模块缺少了fuseforward函数,这里我按照yolov5的源码仓进行了补全
def fuseforward(self, x):
return self.act(self.conv(x))
之后继续进行测试,发现数据集能够正常读取之后又产生了一个新的报错,信息如下图所示,出现在common.py第195行(MF模块forward函数第一行报错),可能还需要您再帮忙check一下,诚盼您的宝贵建议!
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python train.py --cfg models/SRyolo_MF.yaml --super --train_img_size 1024 --hr_input --data data/SRvedai.yaml --ch 64 --input_mode RGB+IR+MF
若使用MF模块,需要将input_mode设置成RGB+IR+MF
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Related Issues (20)
- 之前并没遇到test.py报错,但是今天最近报错了AttributeError: 'Model' object has no attribute 'yaml_file' HOT 1
- 请问论文中表Ⅶ的各算法在多模态下的数据结果您是如何实现的,因为我并没有找到公开的算法代码 HOT 2
- 数据类型报错 HOT 1
- L1loss里的输入参数问题
- 请问MF模块的输入为什么是256尺寸的,imgsz不是1024吗?
- 关于MF过程的疑问 HOT 1
- AttributeError: 'Model' object has no attribute 'steam'
- AttributeError: module 'numpy' has no attribute 'int'. HOT 4
- Question about annotation HOT 2
- test结果 HOT 6
- 请问loss.py中补充的LevelAttention_loss有使用到吗
- 测试使用作者提供的预训练权重问题 HOT 1
- 请问作者在export过程中是否有遇到过索引越界问题,具体问题在commom.py的MF类中 HOT 1
- 测试模型参数和GFLOPs问题 HOT 5
- 作者什么时候能更新superyolo版本的export.py HOT 1
- how super resolution work and where?
- 训练时无法找到标签
- Welcome to SuperYOLO Discussions! HOT 8
- SR的效果如何体现 HOT 3
- why it can't find my images and labels HOT 7
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