Hi @andreas128
Thanks for your great work and sharing the code.
I tried to train SRFlow using REDS dataset. After training the RRDBN network on REDS (with PSNR around 29 dB), I used this config to train SRFlow. However, the resulted SR images are not good and the PSNR is around 17 dB.
I did not change the code by the way. Could you please give me a hint on how can I improve the training?
Hi @andreas128 Thanks for your great work and sharing the code. I tried to train SRFlow using REDS dataset. After training the RRDBN network on REDS (with PSNR around 29 dB), I used this config to train SRFlow. However, the resulted SR images are not good and the PSNR is around 17 dB. I did not change the code by the way. Could you please give me a hint on how can I improve the training?
network_G: which_model_G: SRFlowNet in_nc: 3 out_nc: 3 nf: 64 nb: 25 upscale: 4 train_RRDB: false train_RRDB_delay: 0.5
flow: K: 10 L: 3 noInitialInj: true coupling: CondAffineSeparatedAndCond additionalFlowNoAffine: 2 split: enable: true fea_up0: true stackRRDB: blocks: [ 1,5, 15, 22 ] concat: true
train: manual_seed: 1386 lr_G: !!float 1e-5 weight_decay_G: 0 beta1: 0.9 beta2: 0.99 lr_scheme: MultiStepLR warmup_iter: -1 # no warm up lr_steps_rel: [ 0.5, 0.75, 0.9, 0.95 ] lr_gamma: 0.8 weight_l1: 0.1
niter: 300000 val_freq: !!float 5e3
validation settings
val: heats: [ 0.0, 0.5] n_sample: 1