From 711780126e292ffca984e42005dcfc2e4bc735c5 Mon Sep 17 00:00:00 2001
From: James Betker <jbetker@gmail.com>
Date: Thu, 3 Dec 2020 23:42:51 -0700
Subject: [PATCH] Cleanup

---
 codes/models/networks.py               |  7 -------
 codes/scripts/extract_square_images.py | 10 +++++-----
 2 files changed, 5 insertions(+), 12 deletions(-)

diff --git a/codes/models/networks.py b/codes/models/networks.py
index 3205dd54..c77d435e 100644
--- a/codes/models/networks.py
+++ b/codes/models/networks.py
@@ -125,13 +125,6 @@ def define_G(opt, opt_net, scale=None):
         netG = stylegan2.StyleGan2GeneratorWithLatent(image_size=opt_net['image_size'], latent_dim=opt_net['latent_dim'],
                                             style_depth=opt_net['style_depth'], structure_input=is_structured,
                                             attn_layers=attn)
-    elif which_model == 'srflow':
-        from models.archs.srflow import SRFlow_arch
-        netG = SRFlow_arch.SRFlowNet(in_nc=3, out_nc=3, nf=opt_net['nf'], nb=opt_net['nb'],
-                                     quant=opt_net['quant'], flow_block_maps=opt_net['rrdb_block_maps'],
-                                     noise_quant=opt_net['noise_quant'], hidden_channels=opt_net['nf'],
-                                     K=opt_net['K'], L=opt_net['L'], train_rrdb_at_step=opt_net['rrdb_train_step'],
-                                     hr_img_shape=opt_net['hr_shape'], scale=opt_net['scale'])
     elif which_model == 'srflow_orig':
         from models.archs.srflow_orig import SRFlowNet_arch
         netG = SRFlowNet_arch.SRFlowNet(in_nc=3, out_nc=3, nf=opt_net['nf'], nb=opt_net['nb'], scale=opt_net['scale'],
diff --git a/codes/scripts/extract_square_images.py b/codes/scripts/extract_square_images.py
index f037733e..4f60cab8 100644
--- a/codes/scripts/extract_square_images.py
+++ b/codes/scripts/extract_square_images.py
@@ -13,15 +13,15 @@ import torch
 def main():
     split_img = False
     opt = {}
-    opt['n_thread'] = 20
+    opt['n_thread'] = 10
     opt['compression_level'] = 90  # JPEG compression quality rating.
     # CV_IMWRITE_PNG_COMPRESSION from 0 to 9. A higher value means a smaller size and longer
     # compression time. If read raw images during training, use 0 for faster IO speed.
 
     opt['dest'] = 'file'
-    opt['input_folder'] = ['F:\\4k6k\datasets\\images\\youtube\\videos\\4k_quote_unquote\\images']
-    opt['save_folder'] = 'F:\\4k6k\\datasets\\images\\ge_full_1024'
-    opt['imgsize'] = 1024
+    opt['input_folder'] = ['F:\\4k6k\\datasets\\ns_images\\other_ns']
+    opt['save_folder'] = 'F:\\4k6k\\datasets\\ns_images\\512_unsupervised'
+    opt['imgsize'] = 512
 
     save_folder = opt['save_folder']
     if not osp.exists(save_folder):
@@ -53,7 +53,7 @@ class TiledDataset(data.Dataset):
             return None
         h, w, c = img.shape
         # Uncomment to filter any image that doesnt meet a threshold size.
-        if min(h,w) < 1024:
+        if min(h,w) < 512:
             return None
 
         # We must convert the image into a square.