Comments (1)
Please try this setting:
# @package ds
class: img_dataset
name: MSEC
input:
- /public/hywang26/ds/msec/train/INPUT_IMAGES/*_0.JPG
- /public/hywang26/ds/msec/train/INPUT_IMAGES/*_N1.JPG
- /public/hywang26/ds/msec/train/INPUT_IMAGES/*_N1.5.JPG
- /public/hywang26/ds/msec/train/INPUT_IMAGES/*_P1.JPG
- /public/hywang26/ds/msec/train/INPUT_IMAGES/*_P1.5.JPG
GT:
- /public/hywang26/ds/msec/train/GT_IMAGES/*
- /public/hywang26/ds/msec/train/GT_IMAGES/*
- /public/hywang26/ds/msec/train/GT_IMAGES/*
- /public/hywang26/ds/msec/train/GT_IMAGES/*
- /public/hywang26/ds/msec/train/GT_IMAGES/*
which will extend GT 5 times, one for each input image subset.
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Related Issues (20)
- Excuse me, is there an easy way to use the pretrained model? HOT 3
- Test.py execution problem HOT 2
- May I know what is the average time for validating one image? HOT 1
- 运行test.py时报错使用您提供的预训练模型 HOT 1
- Test.py Error HOT 3
- Dark-Video enhancement HOT 1
- How to draw the input-ground truth luminance mapping curve? HOT 2
- How to cancel the distributed training?
- test problem HOT 4
- test issue
- test HOT 6
- out of memory HOT 6
- prepare_data HOT 1
- Enhanced images with light sources have artifact HOT 3
- Error when trying to run train.py HOT 1
- test problem HOT 9
- Test-GT HOT 3
- Pink pixels HOT 3
- The weight of the loss function HOT 2
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