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icey-zhang avatar icey-zhang commented on August 31, 2024

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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River-Cold avatar River-Cold commented on August 31, 2024

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!

image

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icey-zhang avatar icey-zhang commented on August 31, 2024

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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