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多尺度测试(multi-scale test)中的问题 #1044
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这样的配置无法跑通,请问我该如何修改呢 |
源码里面貌似没给具体的实现 |
您可能没理解我的意思,mmdetection中多尺度训练不是每隔一定的iterations就随机一个图像尺寸吗,推理时是多个尺度并行推理,然后NoC合框,您这回复并不是多尺度推理的,而是多尺度数据集训练推理的 |
mmrotate里常用的多尺度训练和测试就是离线的,其实是离线多尺度裁剪,这是因为DOTA有裁剪图像的操作,所以实验下来离线的会比在线的有效。mmdet那种在线的方式我没试过支不支持。 |
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What's the feature?
您好,我能顺利的使用multi-scale training的流程,但在测试阶段
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=[(1024, 1024),(1440,900),(900,1440)]
flip=False,
transforms=[
dict(type='RResize',multiscale_mode='value'),
dict(type='Normalize', **img_norm_cfg),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img'])
])
]
Any other context?
No response
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