mrq/DL-Art-School
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89 Commits

Author SHA1 Message Date
James Betker
318a604405 Allow weighting of input data 
This essentially allows you to give some datasets more
importance than others for the purposes of reaching a more
refined network.
 2020-06-04 10:05:21 -06:00
James Betker
90125f5bed Allow blurring to be specified 2020-06-02 08:40:52 -06:00
James Betker
1eb9c5a059 Fix grayscale 2020-05-29 22:04:50 -06:00
James Betker
74b313aaa9 Add grayscale downsampling option 2020-05-29 20:34:00 -06:00
James Betker
6962ccb306 Adjust motion blur 
0 is invalid.
 2020-05-27 13:09:46 -06:00
James Betker
e27a49454e Enable vertical splitting on inference images to support very large resolutions. 2020-05-27 08:04:35 -06:00
James Betker
96ac26a8b7 Allow injection of random low-amplitude noise & motion blur into generator 2020-05-27 08:04:11 -06:00
James Betker
69cbfa2f0c Adjust dataset mutations a bit 
Adjusts the compression artfacts to be more aggressive, and blurring to be less aggressive.
 2020-05-26 13:48:34 -06:00
James Betker
2931142458 Allow multiple gt image dirs 2020-05-25 19:21:09 -06:00
James Betker
4e44b8a1aa Clean up video stuff 2020-05-25 19:20:49 -06:00
James Betker
8464cae168 HQ blurring doesnt actually work right - hq images arent the right size when they are blurred 
Just revert it and blur the lq images..
 2020-05-24 22:32:54 -06:00
James Betker
5fd8749cf2 More updates - need more blurring 2020-05-24 22:13:27 -06:00
James Betker
9627cc2c49 Update HR gaussian blur params 2020-05-24 18:00:31 -06:00
James Betker
2f8b0250b9 Blur HR image before downsizing, when available 2020-05-24 17:18:44 -06:00
James Betker
cc4571eb8d Randomize blur effect 2020-05-24 12:35:41 -06:00
James Betker
27a548c019 Enable blurring via settings 2020-05-24 11:56:39 -06:00
James Betker
90073fc761 Update LQ_dataset to support inference on split image videos 2020-05-23 21:05:49 -06:00
James Betker
74bb0fad33 Allow dataset classes to add noise internally 2020-05-23 21:04:24 -06:00
James Betker
67139602f5 Test modifications 
Allows bifurcating large images put into the test pipeline

This code is fixed and not dynamic. Needs some fixes.
 2020-05-19 09:37:58 -06:00
James Betker
d72e154442 Allow more LQ than GT images in corrupt mode 2020-05-14 20:46:20 -06:00
James Betker
585b05e66b Cap test workers at 10 2020-05-13 09:20:45 -06:00
James Betker
f994466289 Initialize test dataloader with a worker count proportional to the batch size. 2020-05-10 10:49:37 -06:00
James Betker
8969a3ce70 Add capability to start at arbitrary frames 2020-05-10 10:48:05 -06:00
James Betker
dbca0d328c Fix multi-lq bug 2020-05-06 23:16:35 -06:00
James Betker
5c1832e124 Add support for multiple LQ paths 
I want to be able to specify many different transformations onto
the target data; the model should handle them all. Do this by
allowing multiple LQ paths to be selected and the dataset class
selects one at random.
 2020-05-06 17:24:17 -06:00
James Betker
44b89330c2 Support inference across batches, support inference on cpu, checkpoint 
This is a checkpoint of a set of long tests with reduced-complexity networks. Some takeaways:
1) A full GAN using the resnet discriminator does appear to converge, but the quality is capped.
2) Likewise, a combination GAN/feature loss does not converge. The feature loss is optimized but
    the model appears unable to fight the discriminator, so the G-loss steadily increases.

Going forwards, I want to try some bigger models. In particular, I want to change the generator
to increase complexity and capacity. I also want to add skip connections between the
disc and generator.
 2020-05-04 08:48:25 -06:00
James Betker
61d3040cf5 Add doCrop into LQGT 2020-05-02 17:46:30 -06:00
James Betker
3781ea725c Add Resnet Discriminator with BN 2020-04-29 20:51:57 -06:00
James Betker
46f550e42b Change downsample_dataset to do no image modification 
I'm  preprocessing the images myself now. There's no need to have
the dataset do this processing as well.
 2020-04-28 11:50:04 -06:00
James Betker
d95808f4ef Implement downsample GAN 
This bad boy is for a workflow where you train a model on disjoint image sets to
downsample a "good" set of images like a "bad" set of images looks. You then
use that downsampler to generate a training set of paired images for supersampling.
 2020-04-24 00:00:46 -06:00
James Betker
ea54c7618a Print error when image read fails 2020-04-23 23:59:32 -06:00
James Betker
e98d92fc77 Allow test to operate on batches 2020-04-23 23:59:09 -06:00
James Betker
79aff886b5 Modifications that allow developer to explicitly specify a different image set for PIX and feature losses 2020-04-22 10:11:14 -06:00
James Betker
12d92dc443 Add GTLQ dataset 2020-04-22 00:40:38 -06:00
James Betker
4d269fdac6 Support independent PIX dataroot 2020-04-22 00:40:13 -06:00
James Betker
f4b33b0531 Some random fixes/adjustments 2020-04-22 00:38:53 -06:00
James Betker
af5dfaa90d Change GT_size to target_size 2020-04-22 00:37:41 -06:00
XintaoWang
a25ee9464d test w/o GT 2019-09-01 22:20:10 +08:00
XintaoWang
037933ba66 mmsr 2019-08-23 21:42:47 +08:00