update

README.md

@@ -52,6 +52,11 @@ If you find this project useful, please star it. It is the greatest appreciation
 
 [![logo](./docs/img/vggface2_hq_compare.png)](https://github.com/NNNNAI/VGGFace2-HQ)
 
+
+## This project also received support from [SocialBook](https://socialbook.io).
+<!-- [![logo](./simswaplogo/socialbook_logo.2020.357eed90add7705e54a8.svg)](https://socialbook.io) -->
+<img width=30% src="./simswaplogo/socialbook_logo.2020.357eed90add7705e54a8.svg"/>
+
 ## Dependencies
 - python3.6+
 - pytorch1.5+

models/fs_model.py

@@ -59,9 +59,6 @@ def initialize(self, opt):
         self.netG = Generator_Adain_Upsample(input_nc=3, output_nc=3, latent_size=512, n_blocks=9, deep=False)
         self.netG.to(device)
 
-
-
-
         # Id network
         netArc_checkpoint = opt.Arc_path
         netArc_checkpoint = torch.load(netArc_checkpoint, map_location=torch.device("cpu"))

models/models.py

@@ -7,13 +7,9 @@
 
 
 def create_model(opt):
-    if opt.model == 'pix2pixHD':
-        #from .pix2pixHD_model import Pix2PixHDModel, InferenceModel
-        from .fs_model import fsModel
-        model = fsModel()
-    else:
-        from .ui_model import UIModel
-        model = UIModel()
+    #from .pix2pixHD_model import Pix2PixHDModel, InferenceModel
+    from .fs_model import fsModel
+    model = fsModel()
 
     model.initialize(opt)
     if opt.verbose:

models/projected_model.py

@@ -5,7 +5,7 @@
 # Created Date: Wednesday January 12th 2022
 # Author: Chen Xuanhong
 # Email: chenxuanhongzju@outlook.com
-# Last Modified:  Thursday, 21st April 2022 8:13:37 pm
+# Last Modified:  Saturday, 13th May 2023 9:56:35 am
 # Modified By: Chen Xuanhong
 # Copyright (c) 2022 Shanghai Jiao Tong University
 #############################################################
@@ -46,7 +46,7 @@ def initialize(self, opt):
         # Id network
         netArc_checkpoint = opt.Arc_path
         netArc_checkpoint = torch.load(netArc_checkpoint, map_location=torch.device("cpu"))
-        self.netArc = netArc_checkpoint['model'].module
+        self.netArc = netArc_checkpoint
         self.netArc = self.netArc.cuda()
         self.netArc.eval()
         self.netArc.requires_grad_(False)

options/base_options.py

@@ -13,7 +13,7 @@ def initialize(self):
         self.parser.add_argument('--name', type=str, default='people', help='name of the experiment. It decides where to store samples and models')
         self.parser.add_argument('--gpu_ids', type=str, default='0', help='gpu ids: e.g. 0  0,1,2, 0,2. use -1 for CPU')
         self.parser.add_argument('--checkpoints_dir', type=str, default='./checkpoints', help='models are saved here')
-        self.parser.add_argument('--model', type=str, default='pix2pixHD', help='which model to use')
+        # self.parser.add_argument('--model', type=str, default='pix2pixHD', help='which model to use')
         self.parser.add_argument('--norm', type=str, default='batch', help='instance normalization or batch normalization')
         self.parser.add_argument('--use_dropout', action='store_true', help='use dropout for the generator')
         self.parser.add_argument('--data_type', default=32, type=int, choices=[8, 16, 32], help="Supported data type i.e. 8, 16, 32 bit")

options/test_options.py

@@ -24,7 +24,7 @@ def initialize(self):
         self.parser.add_argument("--onnx", type=str, help="run ONNX model via TRT")        
         self.parser.add_argument("--Arc_path", type=str, default='arcface_model/arcface_checkpoint.tar', help="run ONNX model via TRT")
         self.parser.add_argument("--pic_a_path", type=str, default='G:/swap_data/ID/elon-musk-hero-image.jpeg', help="Person who provides identity information")
-        self.parser.add_argument("--pic_b_path", type=str, default='G:/swap_data/ID/bengio.jpg', help="Person who provides information other than their identity")
+        self.parser.add_argument("--pic_b_path", type=str, default='./demo_file/multi_people.jpg', help="Person who provides information other than their identity")
         self.parser.add_argument("--pic_specific_path", type=str, default='./crop_224/zrf.jpg', help="The specific person to be swapped")
         self.parser.add_argument("--multisepcific_dir", type=str, default='./demo_file/multispecific', help="Dir for multi specific")
         self.parser.add_argument("--video_path", type=str, default='G:/swap_data/video/HSB_Demo_Trim.mp4', help="path for the video to swap")
@@ -33,6 +33,6 @@ def initialize(self):
         self.parser.add_argument('--id_thres', type=float, default=0.03, help='how many test images to run')
         self.parser.add_argument('--no_simswaplogo', action='store_true', help='Remove the watermark')
         self.parser.add_argument('--use_mask', action='store_true', help='Use mask for better result')
-        self.parser.add_argument('--crop_size', type=int, default=224, help='Crop of size of input image')
+        self.parser.add_argument('--crop_size', type=int, default=512, help='Crop of size of input image')
 
         self.isTrain = False