Comments (4)
alterzero
commented on August 30, 2024
You can do it.
Basically, you can change num_channels=1
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gittigxuy
commented on August 30, 2024
No,I do not think so,just change num_channels=1,so could you please release a detail example code to train luminance channel data?Thanks
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alterzero
commented on August 30, 2024
Of course you need to convert the train image to luminance only beforehand.
Anyhow, I did not train the network using only luminance channel, but only the evaluation is calculated the PSNR using luminance layer only.
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gittigxuy
commented on August 30, 2024
So,if I train RGB data,and test with luminance channel,does the result same with both Train and Test use luminance channel
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Related Issues (20)
- Result is too big HOT 2
- How to compute the psnr in paper?
- Why is the super-resolution result the same size as input image ? HOT 6
- Can we change nFrames when testing the model
- Use nGPUs for testing
- Missing dependencies on the README HOT 1
- Error loading pretrained model HOT 1
- Unable to use RBPN_4x_F11_NTIRE2019 pretrained model: size mismatch for module.output.conv.weight HOT 1
- Can you provide other nFrames pretrained model like nFrames=3? thanks
- Process finished with exit code -1073741819 (0xC0000005) HOT 2
- Maybe it should be 90
- The PSNR of my result was smallar than paper's,why?
- How do you train the image of one channel?
- Results in MSU Video Super Resolution Benchmark
- TypeError: Variable data has to be a tensor, but got builtin_function_or_method
- How long does the training last? and using what specs?
- How are the weights for 11 frames trained
- Your Results in New Super-Resolution Benchmarks
- Parameters of Upblock
- some question about testing
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