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51 commits

Author SHA1 Message Date
nagadomi 9a89ddd20e remove unused model 2018-11-14 17:40:48 +09:00
nagadomi d5c2277e0e misc 2018-11-14 17:21:34 +09:00
nagadomi dd8cb71601 clean 2018-11-14 07:51:14 +09:00
nagadomi 62770a901a Update cunet arch optimized by benchmark 2018-11-04 08:03:37 +09:00
nagadomi 3654ee41cf Fix shortcut connection order in unet_branch 2018-11-01 20:00:11 +09:00
nagadomi 2e59d97b17 Temporary added experimental models 2018-11-01 19:59:07 +09:00
nagadomi 804896276e Remove SEBlock from the first layer 2018-10-31 07:04:30 +00:00
nagadomi 9d924acbe5 Add cunet_s 2018-10-31 01:02:28 +09:00
nagadomi 3e4058821e SEBlock test tmp 2018-10-30 14:44:28 +00:00
nagadomi 6efd7f890e Add cunet for 1x; Remove unused code 2018-10-29 04:07:05 +09:00
nagadomi b28b6172ca clean; Add upcunet_v3 2018-10-28 16:03:52 +09:00
nagadomi 17b8de2d36 Make the performance benchmark practical 2018-10-27 20:38:04 +09:00
nagadomi 2d85f70415 Add support for w2nn_valid_input_size 2018-10-27 08:00:23 +00:00
nagadomi 8051535fdc nobias 2018-10-27 06:05:10 +00:00
nagadomi 0b82668359 Add upcunet_v2, fixed the Global AVE problem 2018-10-27 14:59:51 +09:00
nagadomi 1f18d1919a clean 2018-10-25 11:44:55 +00:00
nagadomi 06246e0d78 refactor 2018-10-21 00:56:39 +00:00
nagadomi ef5aa1ccbb SEBlock 2018-10-18 19:49:10 +00:00
nagadomi 4b9196deaa cunet_v5 2018-10-16 13:02:42 +00:00
nagadomi e6da46d08f experimental model 2018-10-14 01:21:23 +09:00
nagadomi 05bc54fa12 Add support for identity initializer for dilated convolution, and refactor 2017-04-21 08:54:39 +09:00
nagadomi 763f5ddcab Fix crop bug in rare case 2017-02-12 17:46:07 +09:00
nagadomi 3447c6c44c rename srresnet_12l to resnet_14l because it's not the same as SRResNet 2017-01-21 16:53:10 +09:00
nagadomi 742c9fdd95 disable gcn 2017-01-09 12:51:45 +09:00
nagadomi 43a9b58fcb Add GCN option for user method 2016-12-25 20:17:47 +09:00
nagadomi 61f2abd632 remove unused code 2016-11-09 03:10:54 +09:00
nagadomi f088af9606 add srresnet_12l 2016-11-09 03:06:57 +09:00
nagadomi c8271af3ab add srresnet_12l 2016-11-09 03:06:26 +09:00
nagadomi 4be1141292 Fix srresnet_2x 2016-11-06 01:19:20 +09:00
nagadomi bdaca16c67 perfomance tuning 2016-11-02 23:42:14 +09:00
nagadomi 74ed227f48 Update fcn_v1 2016-10-24 09:10:17 +09:00
nagadomi 1e80e45a03 add experimental models 2016-10-20 23:41:39 +09:00
nagadomi a604aa3b7a Add some experimental model 2016-10-08 17:21:01 +09:00
nagadomi cabeeed2a7 Add Clip(0,1) to last layer 2016-09-14 21:23:29 +09:00
nagadomi 9563d84302 No bias at FullConvolution 2016-07-12 11:15:12 +09:00
nagadomi 51914b894a change weight initialization and upconv_7 2016-06-08 06:58:46 +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 48411a4dde refactor 2016-05-14 16:51:36 +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 7af5c9443d Add model option and 12 layers net 2016-04-23 09:19:03 +09:00
nagadomi fd06a47d56 Fix clearState 2016-03-28 18:38:31 +09:00
nagadomi 4a1629d046 More clearState for nn.SpatialConvolutionMM 2016-03-12 07:25:16 +09:00
nagadomi 56582b8401 Fix error in training script due to missing libcudnn.so 2015-12-09 07:04:04 +09:00
nagadomi f7b298690d Fix the missing initialization function
I don't know why was this function removed.
2015-11-18 21:46:43 +09:00
nagadomi 21ea5dd858 add cudnn converter 2015-10-29 18:05:33 +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 d8ca857a82 change initial weights 2015-07-11 14:52:51 +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