support model config during inference

inference_realesrgan.py

@@ -2,6 +2,7 @@ import argparse
 import cv2
 import glob
 import os
+from basicsr.archs.rrdbnet_arch import RRDBNet
 
 from realesrgan import RealESRGANer
 
@@ -18,11 +19,12 @@ def main():
     parser.add_argument('--netscale', type=int, default=4, help='Upsample scale factor of the network')
     parser.add_argument('--outscale', type=float, default=4, help='The final upsampling scale of the image')
     parser.add_argument('--suffix', type=str, default='out', help='Suffix of the restored image')
-    parser.add_argument('--tile', type=int, default=800, help='Tile size, 0 for no tile during testing')
+    parser.add_argument('--tile', type=int, default=0, help='Tile size, 0 for no tile during testing')
     parser.add_argument('--tile_pad', type=int, default=10, help='Tile padding')
     parser.add_argument('--pre_pad', type=int, default=0, help='Pre padding size at each border')
     parser.add_argument('--face_enhance', action='store_true', help='Use GFPGAN to enhance face')
     parser.add_argument('--half', action='store_true', help='Use half precision during inference')
+    parser.add_argument('--block', type=int, default=23, help='num_block in RRDB')
     parser.add_argument(
         '--alpha_upsampler',
         type=str,
@@ -35,9 +37,17 @@ def main():
         help='Image extension. Options: auto | jpg | png, auto means using the same extension as inputs')
     args = parser.parse_args()
 
+    if 'RealESRGAN_x4plus_anime_6B.pth' in args.model_path:
+        args.block = 6
+    elif 'RealESRGAN_x2plus.pth' in args.model_path:
+        args.netscale = 2
+
+    model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=args.block, num_grow_ch=32, scale=args.netscale)
+
     upsampler = RealESRGANer(
         scale=args.netscale,
         model_path=args.model_path,
+        model=model,
         tile=args.tile,
         tile_pad=args.tile_pad,
         pre_pad=args.pre_pad,

realesrgan/utils.py

@@ -13,7 +13,7 @@ ROOT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
 
 class RealESRGANer():
 
-    def __init__(self, scale, model_path, tile=0, tile_pad=10, pre_pad=10, half=False):
+    def __init__(self, scale, model_path, model=None, tile=0, tile_pad=10, pre_pad=10, half=False):
         self.scale = scale
         self.tile_size = tile
         self.tile_pad = tile_pad
@@ -23,7 +23,8 @@ class RealESRGANer():
 
         # initialize model
         self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-        model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=scale)
+        if model is None:
+            model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=scale)
 
         if model_path.startswith('https://'):
             model_path = load_file_from_url(