Comments (6)
混合训练:RGB+IR+MF,单独训练:IR
这是混合训练的图,上一张是IR训练的图,都是RGB的呀,没有红外线的图,这是啥问题?
from superyolo.
您好,这是因为训练的可视化的时候,用的都是RGB的图,你可以看train.py 第144行:
Line 444 in 481322d
测试的时候是分开了的,你可以看test.py 第245行
Line 245 in 481322d
from superyolo.
您好,这是因为训练的可视化的时候,用的都是RGB的图,你可以看 train.py 第144行:
Line 444 in 481322d
测试的时候是分开了的,你可以看 test.py 第245行
Line 245 in 481322d
也就是说,训练是RGB和IR一块训练的,只不过可视化是只显示了RGB图像?
from superyolo.
???作者可以回答一下吗?麻烦您了
from superyolo.
多模态的时候是在RGB上做了可视化
from superyolo.
为啥低分辨率的val,使用SR后效果并不好,还不如高分辨率的val
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Related Issues (20)
- 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
- About multimodal results on YOLOv5
- 请问VEDAI数据集为什么在论文结果对比和代码中只保留了8类,删去了vehicle呢?
- SR网络 HOT 1
- Tag corresponding category HOT 1
- SR分支 HOT 1
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from superyolo.