update inference_video: support auto download

inference_realesrgan_video.py

@@ -8,6 +8,7 @@ import shutil
 import subprocess
 import torch
 from basicsr.archs.rrdbnet_arch import RRDBNet
+from basicsr.utils.download_util import load_file_from_url
 from os import path as osp
 from tqdm import tqdm
 
@@ -172,32 +173,55 @@ class Writer:
 def inference_video(args, video_save_path, device=None, total_workers=1, worker_idx=0):
     # ---------------------- determine models according to model names ---------------------- #
     args.model_name = args.model_name.split('.pth')[0]
-    if args.model_name in ['RealESRGAN_x4plus', 'RealESRNet_x4plus']:  # x4 RRDBNet model
+    if args.model_name == 'RealESRGAN_x4plus':  # x4 RRDBNet model
         model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
         netscale = 4
-    elif args.model_name in ['RealESRGAN_x4plus_anime_6B']:  # x4 RRDBNet model with 6 blocks
+        file_url = ['https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth']
+    elif args.model_name == 'RealESRNet_x4plus':  # x4 RRDBNet model
+        model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
+        netscale = 4
+        file_url = ['https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.1/RealESRNet_x4plus.pth']
+    elif args.model_name == 'RealESRGAN_x4plus_anime_6B':  # x4 RRDBNet model with 6 blocks
         model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=6, num_grow_ch=32, scale=4)
         netscale = 4
-    elif args.model_name in ['RealESRGAN_x2plus']:  # x2 RRDBNet model
+        file_url = ['https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth']
+    elif args.model_name == 'RealESRGAN_x2plus':  # x2 RRDBNet model
         model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=2)
         netscale = 2
-    elif args.model_name in ['realesr-animevideov3']:  # x4 VGG-style model (XS size)
+        file_url = ['https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth']
+    elif args.model_name == 'realesr-animevideov3':  # x4 VGG-style model (XS size)
         model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=16, upscale=4, act_type='prelu')
         netscale = 4
-    else:
-        raise NotImplementedError
+        file_url = ['https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-animevideov3.pth']
+    elif args.model_name == 'realesr-general-x4v3':  # x4 VGG-style model (S size)
+        model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
+        netscale = 4
+        file_url = [
+            'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-wdn-x4v3.pth',
+            'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth'
+        ]
 
     # ---------------------- determine model paths ---------------------- #
-    model_path = os.path.join('experiments/pretrained_models', args.model_name + '.pth')
-    if not os.path.isfile(model_path):
-        model_path = os.path.join('weights', args.model_name + '.pth')
+    model_path = os.path.join('weights', args.model_name + '.pth')
     if not os.path.isfile(model_path):
-        raise ValueError(f'Model {args.model_name} does not exist.')
+        ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
+        for url in file_url:
+            # model_path will be updated
+            model_path = load_file_from_url(
+                url=url, model_dir=os.path.join(ROOT_DIR, 'weights'), progress=True, file_name=None)
+
+    # use dni to control the denoise strength
+    dni_weight = None
+    if args.model_name == 'realesr-general-x4v3' and args.denoise_strength != 1:
+        wdn_model_path = model_path.replace('realesr-general-x4v3', 'realesr-general-wdn-x4v3')
+        model_path = [model_path, wdn_model_path]
+        dni_weight = [args.denoise_strength, 1 - args.denoise_strength]
 
     # restorer
     upsampler = RealESRGANer(
         scale=netscale,
         model_path=model_path,
+        dni_weight=dni_weight,
         model=model,
         tile=args.tile,
         tile_pad=args.tile_pad,
@@ -312,9 +336,16 @@ def main():
         type=str,
         default='realesr-animevideov3',
         help=('Model names: realesr-animevideov3 | RealESRGAN_x4plus_anime_6B | RealESRGAN_x4plus | RealESRNet_x4plus |'
-              ' RealESRGAN_x2plus | '
+              ' RealESRGAN_x2plus | realesr-general-x4v3'
               'Default:realesr-animevideov3'))
     parser.add_argument('-o', '--output', type=str, default='results', help='Output folder')
+    parser.add_argument(
+        '-dn',
+        '--denoise_strength',
+        type=float,
+        default=0.5,
+        help=('Denoise strength. 0 for weak denoise (keep noise), 1 for strong denoise ability. '
+              'Only used for the realesr-general-x4v3 model'))
     parser.add_argument('-s', '--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 video')
     parser.add_argument('-t', '--tile', type=int, default=0, help='Tile size, 0 for no tile during testing')