add realsr docs (#159)

configs/realsr_bicubic_noise_x4_df2k.yaml

@@ -34,8 +34,8 @@ model:
 dataset:
   train:
     name: SRDataset
-    gt_folder: data/realsr_preprocess/DF2K/generated/tdsr/HR_sub/
-    lq_folder: data/realsr_preprocess/DF2K/generated/tdsr/LR_sub/
+    gt_folder: data/DF2K/generated/tdsr/HR/
+    lq_folder: data/DF2K/generated/tdsr/LR/
     num_workers: 4
     batch_size: 16
     scale: 4
@@ -64,7 +64,7 @@ dataset:
             std: [255., 255., 255.]
             keys: [image, image]
           - name: SRNoise
-            noise_path: data/realsr_preprocess/DF2K/Corrupted_noise/
+            noise_path: data/DF2K/Corrupted_noise/
             size: 32
             keys: [image]
   test:

configs/realsr_kernel_noise_x4_dped.yaml

@@ -34,8 +34,8 @@ model:
 dataset:
   train:
     name: SRDataset
-    gt_folder: data/realsr_preprocess/DPED/generated/clean/train_tdsr/HR/
-    lq_folder: data/realsr_preprocess/DPED/generated/clean/train_tdsr/LR/
+    gt_folder: data/DPED/generated/clean/train_tdsr/HR/
+    lq_folder: data/DPED/generated/clean/train_tdsr/LR/
     num_workers: 4
     batch_size: 16
     scale: 4
@@ -64,7 +64,7 @@ dataset:
             std: [255., 255., 255.]
             keys: [image, image]
           - name: SRNoise
-            noise_path: data/realsr_preprocess/DPED/DPEDiphone_noise/
+            noise_path: data/DPED/DPEDiphone_noise/
             size: 32
             keys: [image]
   test:

data/realsr_preprocess/collect_noise.py

@@ -27,7 +27,8 @@ parser.add_argument('--upscale_factor',
 opt = parser.parse_args()
 
 # define input and target directories
-with open('./preprocess/paths.yml', 'r') as stream:
+cur_path = os.path.abspath(os.path.dirname(__file__))
+with open(os.path.join(cur_path, './paths.yml'), 'r') as stream:
     PATHS = yaml.load(stream)
 
 

data/realsr_preprocess/create_bicubic_dataset.py

@@ -48,7 +48,8 @@ parser.add_argument('--upscale_factor',
 opt = parser.parse_args()
 
 # define input and target directories
-with open('./paths.yml', 'r') as stream:
+cur_path = os.path.abspath(os.path.dirname(__file__))
+with open(os.path.join(cur_path, './paths.yml'), 'r') as stream:
     PATHS = yaml.load(stream)
 
 if opt.dataset == 'df2k':
@@ -82,7 +83,8 @@ else:
 tdsr_hr_dir = path_tdsr + 'HR'
 tdsr_lr_dir = path_tdsr + 'LR'
 
-assert not os.path.exists(PATHS['datasets'][opt.dataset])
+assert not os.path.exists(tdsr_hr_dir)
+assert not os.path.exists(tdsr_lr_dir)
 
 if not os.path.exists(tdsr_hr_dir):
     os.makedirs(tdsr_hr_dir)

data/realsr_preprocess/paths.yml

 df2k:
   tdsr:
-    source: '/workspace/datasets/ntire20/Corrupted-tr-x'
-    target: '/workspace/datasets/ntire20/Corrupted-tr-y'
+    source: './data/ntire20/Corrupted-tr-x'
+    target: './data/ntire20/Corrupted-tr-y'
     valid:
 dped:
   clean:
     hr:
-      train: '/workspace/datasets/ntire20/DPEDiphone-tr-x'
-      valid: '/workspace/datasets/ntire20/DPEDiphone-va'
+      train: './data/ntire20/DPEDiphone-tr-x'
+      valid: './data/datasets/ntire20/DPEDiphone-va'
 datasets:
-  df2k: 'DF2K'
-  dped: 'DPED'
+  df2k: 'data/DF2K'
+  dped: 'data/DPED'

docs/en_US/tutorials/super_resolution.md

@@ -52,6 +52,16 @@
     python data/process_div2k_data.py --data-root data/DIV2K
   ```
 
+  Prepare dataset for realsr df2k model:
+  Download dataset from [NTIRE 2020 RWSR](https://competitions.codalab.org/competitions/22220#participate) and unzip it to your path.
+  Unzip Corrupted-tr-x.zip and Corrupted-tr-y.zip to ``PaddleGAN/data/ntire20`` directory.
+
+  Run the following commands:
+  ```
+    python ./data/realsr_preprocess/create_bicubic_dataset.py --dataset df2k --artifacts tdsr
+
+    python ./data/realsr_preprocess/collect_noise.py --dataset df2k --artifacts tdsr
+  ```
 
 ### 1.2.2 Train/Test