DL-Art-School/codes
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
..
data Support inference across batches, support inference on cpu, checkpoint 2020-05-04 08:48:25 -06:00
data_scripts Some random fixes/adjustments 2020-04-22 00:38:53 -06:00
metrics mmsr 2019-08-23 21:42:47 +08:00
models Support inference across batches, support inference on cpu, checkpoint 2020-05-04 08:48:25 -06:00
options Support inference across batches, support inference on cpu, checkpoint 2020-05-04 08:48:25 -06:00
scripts mmsr 2019-08-23 21:42:47 +08:00
temp Add colab option 2020-05-02 17:47:25 -06:00
utils mmsr 2019-08-23 21:42:47 +08:00
requirements.txt Create requirements.txt 2019-11-24 07:48:52 +00:00
run_scripts.sh mmsr 2019-08-23 21:42:47 +08:00
test_Vid4_REDS4_with_GT_DUF.py mmsr 2019-08-23 21:42:47 +08:00
test_Vid4_REDS4_with_GT_TOF.py mmsr 2019-08-23 21:42:47 +08:00
test_Vid4_REDS4_with_GT.py mmsr 2019-08-23 21:42:47 +08:00
test.py Support inference across batches, support inference on cpu, checkpoint 2020-05-04 08:48:25 -06:00
train.py Fixup upconv for the next attempt! 2020-05-01 19:56:14 -06:00