mrq/DL-Art-School
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339 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