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10 commits

Author SHA1 Message Date
nagadomi 96bf23b29e Fix cudnn -> cunn 2016-08-07 01:59:17 +09:00
nagadomi 7040dff6f8 Fix noise0 model (backend: cudnn -> cunn) 2016-08-07 01:41:42 +09:00
nagadomi 93511a2a9f Update upconv_7/art/scale2.0x model; Fix mesh-artifact 2016-07-30 05:16:02 +09:00
nagadomi 3b728643ec Update upconv_7 models; bias term in last layer is removed 2016-07-21 20:41:48 +09:00
nagadomi 9563d84302 No bias at FullConvolution 2016-07-12 11:15:12 +09:00
nagadomi cbe1874be3 Add noise0 model to photo/art 2016-07-09 09:06:51 +09:00
nagadomi ca6786b9dc Add upconv_7/photo models. Update vgg_7/photo/noise* models 2016-07-04 04:51:22 +09:00
nagadomi 708447a246 Update pretrained models. support for yuv420 jpeg 2016-06-20 15:58:11 +09:00
nagadomi a545bcffbd Update models/upconv_7/art 2016-06-13 14:54:26 +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