Comments (9)
superxmmdm
commented on August 21, 2024
2
您具体什么问题呢？我这边基本问题都解决了。
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主题: Re: [hanna-xu/DDcGAN] 我在训练多分辨率融合时遇到一个问题 (#14)
您好, 我也遇到了一样的问题,不知道这个问题有没有相关解决方法呢？
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superxmmdm
commented on August 21, 2024
我遇到了同样的问题，请问您解决了吗？
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Xyler6561
commented on August 21, 2024
您好, 我也遇到了一样的问题,不知道这个问题有没有相关解决方法呢？
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hanna-xu
commented on August 21, 2024
数据维度不一致造成的，建议交换数据维度
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lmydream
commented on August 21, 2024
我也遇到了这个问题，请问您是怎么解决的呢？非常感谢
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1214083397
commented on August 21, 2024
建议修改为：
VIS_batch = source_imgs[batch * BATCH_SIZE:(batch * BATCH_SIZE + BATCH_SIZE), 0, :, :]
ir_or_batch = source_imgs[batch * BATCH_SIZE:(batch * BATCH_SIZE + BATCH_SIZE), 1, :, :]
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1214083397
commented on August 21, 2024
ir_batch[b, :, :] = scipy.ndimage.zoom(ir_or_batch[b, :, :], 0.25)ValueError: could not broadcast input array from shape (0,21) into shape (21,21)
执行的过程中报了这个错误。请问应该如何处理
建议修改为：
VIS_batch = source_imgs[batch * BATCH_SIZE:(batch * BATCH_SIZE + BATCH_SIZE), 0, :, :]
ir_or_batch = source_imgs[batch * BATCH_SIZE:(batch * BATCH_SIZE + BATCH_SIZE), 1, :, :]
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1214083397
commented on August 21, 2024
我也遇到了这个问题，请问您是怎么解决的呢？非常感谢
建议修改为：
VIS_batch = source_imgs[batch * BATCH_SIZE:(batch * BATCH_SIZE + BATCH_SIZE), 0, :, :]
ir_or_batch = source_imgs[batch * BATCH_SIZE:(batch * BATCH_SIZE + BATCH_SIZE), 1, :, :]
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lmydream
commented on August 21, 2024
数据维度不一致造成的，建议交换数据维度
想用自己的数据集跑same-resolution vis-ir image fusion的图像融合，然后把一张源图像分为若干个84X84patch组成数据集，但是训练结果非常非常差，请问一下这是我数据集制作的错误吗
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Related Issues (20)
- hi,I have some questions about the data set, can you help me? HOT 3
- Question about dataset HOT 6
- there is an error when I run your model HOT 6
- How can I improve it? HOT 3
- 对于数据集的问题 HOT 1
- Can I get a dataset in another way?
- About the metrics
- Try with .nii images
- about The MRI/PET
- What to do if you want to change a data set
- Training data encountered a problem
- about multi-ressolution testing
- Does it can be used for the fusion of RGB image and infrared image? HOT 1
- What are the dependencies used?
- session问题
- 训练模型是出现一个问题 HOT 4
- 自己训练为什么会出现G_loss: nan, D1_loss: nan, D2_loss: nan HOT 3
- GPU使用
- Is there a code for test.py HOT 1
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