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51 commits

Author SHA1 Message Date
nagadomi e5cfd3dfce Add -resume option 2016-06-09 02:39:52 +09:00
nagadomi 6c758ec5c0 Correct messages 2016-06-08 07:52:38 +09:00
nagadomi 307ae40883 Add noise_scale training 2016-06-08 06:39:36 +09:00
nagadomi d0630d3a20 individual filters and box-only support 2016-06-06 14:04:13 +09:00
nagadomi c89fd7249a Add learning_rate_decay 2016-06-02 10:11:15 +09:00
nagadomi 634046d5f0 Fix training mode 2016-05-29 05:50:53 +09:00
nagadomi b96bc5d453 Use correct criterion 2016-05-28 10:56:15 +09:00
nagadomi 8088460a20 Add oracle_rate option 2016-05-27 16:54:29 +09:00
nagadomi 8fec6f1b5a Change the learning rate decay rate 2016-05-21 09:56:26 +09:00
nagadomi 7814691cbf Add resize_blur parameter
latest graphicsmagick is required
2016-05-21 09:54:12 +09:00
nagadomi a210090033 Convert model files; Add new pretrained model
- Add new pretrained model to ./models/upconv_7
- Move old models to ./models/vgg_7
- Use nn.LeakyReLU instead of w2nn.LeakyReLU
- Add useful attribute to .json

New JSON attribute:
The first layer has `model_config` attribute.
It contains:
  model_arch: architecture name of model. see `lib/srcnn.lua`
  scale_factor: if scale_factor > 1, model:forward() changes image resolution with scale_factor.
  channels: input/output channels. if channels == 3, model is RGB model.
  offset: pixel size that is to be removed from output.
          for example:
            (scale_factor=1, offset=7, input=100x100) => output=(100-7)x(100-7)
            (scale_factor=2, offset=12, input=100x100) => output=(100*2-12)x(100*2-12)
And each layer has `class_name` attribute.
2016-05-15 03:04:08 +09:00
nagadomi 51ae485cd1 Add new models
upconv_7 is 2.3x faster than previous model
2016-05-13 09:49:53 +09:00
nagadomi b8088ca209 Remove the limit of learning_rate_decay 2016-04-30 13:48:24 +09:00
nagadomi 7af5c9443d Add model option and 12 layers net 2016-04-23 09:19:03 +09:00
nagadomi 68a6d4cef5 Use MSE instead of PSNR
PSNR depends on the minibatch size and those group.
2016-04-17 02:08:38 +09:00
nagadomi fa9355be7c Fix validation metric 2016-04-16 03:52:05 +09:00
nagadomi a92b2cb386 Fix progressbar 2016-04-16 03:45:21 +09:00
nagadomi ea780f1871 Fix validation metric 2016-04-16 03:23:37 +09:00
nagadomi 30fe5db735 Add upsampling_filter option 2016-04-02 22:03:27 +09:00
nagadomi 13f702b968 Add support for resizing with gamma correction 2016-03-28 19:07:09 +09:00
nagadomi d4833160c7 Optionalize downsampling filters 2016-03-17 17:58:37 +09:00
nagadomi 4d115e4bdb Add support for plotting loss chart 2016-03-14 05:06:14 +09:00
nagadomi 459c7c5e18 Use similar distribution on train/validation 2016-03-12 08:50:55 +09:00
nagadomi 1900ac7500 Use PSNR for evaluation 2016-03-12 06:53:42 +09:00
nagadomi 664322fa97 Remove cleanup_model.lua; Change model format from binary to ascii 2016-03-12 05:20:19 +09:00
nagadomi 290a5f960b Use Huber loss instead of MSE 2016-03-11 11:13:45 +09:00
nagadomi 9b238bd693 Use clearState() 2016-03-11 11:12:02 +09:00
nagadomi 9f935835dd Add -save_history option 2015-12-04 18:49:34 +09:00
nagadomi aaac6ed6e5 Refactor training loop
more shuffle
2015-11-30 17:18:52 +09:00
nagadomi c72ec3112b Add -random_unsharp_mask_rate option for photo 2015-11-27 18:36:36 +09:00
nagadomi d8ba661d6b Add -jpeg_chroma_subsampling_rate option for JPEG denoise training 2015-11-26 17:10:57 +09:00
nagadomi 42bd89151e Add -gpu option in train.lua 2015-11-13 19:26:58 +09:00
nagadomi 5ab2c605c8 Fix header include order issues 2015-11-08 18:31:46 +09:00
nagadomi 797b45ae23 Use roundf-like clip for 8 bit-depth image
Maybe PSNR +0.03 improved by this commit
2015-11-08 05:44:14 +09:00
nagadomi 3ea16b3b86 tunable parameters 2015-11-07 07:18:22 +09:00
nagadomi c773e18e59 Add trade-off parameter for noise reduction 2015-11-07 06:37:53 +09:00
nagadomi 903d945652 cleanup 2015-11-06 10:08:54 +09:00
nagadomi b35a9ae7d7 tuning 2015-11-03 06:10:44 +09:00
nagadomi 490eb33a6b Minimize the weighted huber loss instead of the weighted mean square error
Huber loss is less sensitive to outliers(i.e. noise) in data than the squared error loss.
2015-10-31 22:05:59 +09:00
nagadomi da786e15ba remove noise_scale training 2015-10-28 16:27:31 +09:00
nagadomi 3abc5a03e3 refactor 2015-10-28 16:01:07 +09:00
nagadomi 8dea362bed sync from internal repo
- Memory compression by snappy (lua-csnappy)
- Use RGB-wise Weighted MSE(R*0.299, G*0.587, B*0.114) instead of MSE
- Aggressive cropping for edge region
and some change.
2015-10-26 09:23:52 +09:00
nagadomi 54580ba8c0 add data augmentation method that uses overlay 2015-08-02 22:02:14 +09:00
nagadomi e3d3a8355c change training script
- add AlexNet's color noise (default: false)
- add `photo` category for noise level setting
2015-07-11 21:57:04 +09:00
nagadomi fd9dadd7a4 use settings.validation_crop 2015-06-26 20:12:51 +09:00
nagadomi 5b4d692f03 add support for RGB color space reconstruction
- add new RGB model (models/anime_style_art_rgb).
- RGB model can reduce color noise.
- waifu2x uses this RGB model by default.

You can use Y model with:
$ th waifu2x.lua -model_dir models/anime_style_art -i input.png -o output.png
$ th train.lua -color y ...
2015-06-23 02:55:30 +09:00
nagadomi a706892b59 merge develop repo
- remove support for cuDNN
- add new pre-trained model and json files
- some changes in training script

If you have cuDNN model, Please run following commands to convert.
$ cp models/your_own_model.t7 models/your_own_model.t7.backup
$ th cudnn2cunn.lua -model models/your_own_model.t7
2015-06-13 15:20:40 +09:00
nagadomi 1c1f2292d1 fix ugly chroma scaling 2015-05-22 20:06:25 +09:00
nagadomi ffd52fdb2b super typo fix 2015-05-19 16:47:52 +09:00
nagadomi 2231423056 update training script 2015-05-17 14:43:07 +09:00