Demo files

data_config.py

@@ -11,8 +11,10 @@ def get_data_config(self, data_name):
         elif data_name == 'DSIFN':
             self.label_transform = "norm"
             self.root_dir = '/media/lidan/ssd2/CDData/DSIFN_256/'
-        elif data_name == 'quick_start':
-            self.root_dir = './samples/'
+        elif data_name == 'quick_start_LEVIR':
+            self.root_dir = './samples_LEVIR/'
+        elif data_name == 'quick_start_DSIFN':
+            self.root_dir = './samples_DSIFN/'
         else:
             raise TypeError('%s has not defined' % data_name)
         return self

demo_DSIFN.py

@@ -0,0 +1,80 @@
+from argparse import ArgumentParser
+
+import utils
+import torch
+from models.basic_model import CDEvaluator
+
+import os
+
+"""
+quick start
+
+sample files in ./samples
+
+save prediction files in the ./samples/predict
+
+"""
+
+
+def get_args():
+    # ------------
+    # args
+    # ------------
+    parser = ArgumentParser()
+    parser.add_argument('--project_name', default='ChangeFormer_DSIFN', type=str)
+    parser.add_argument('--gpu_ids', type=str, default='0', help='gpu ids: e.g. 0  0,1,2, 0,2. use -1 for CPU')
+    parser.add_argument('--checkpoint_root', default='checkpoints', type=str)
+    parser.add_argument('--output_folder', default='samples_DSIFN/predict', type=str)
+
+    # data
+    parser.add_argument('--num_workers', default=0, type=int)
+    parser.add_argument('--dataset', default='CDDataset', type=str)
+    parser.add_argument('--data_name', default='quick_start_DSIFN', type=str)
+
+    parser.add_argument('--batch_size', default=1, type=int)
+    parser.add_argument('--split', default="demo", type=str)
+    parser.add_argument('--img_size', default=256, type=int)
+
+    # model
+    parser.add_argument('--n_class', default=2, type=int)
+    parser.add_argument('--embed_dim', default=256, type=int)
+    parser.add_argument('--net_G', default='ChangeFormerV6', type=str,
+                        help='ChangeFormerV6 | base_resnet18 | base_transformer_pos_s4_dd8 | base_transformer_pos_s4_dd8_dedim8|')
+    parser.add_argument('--checkpoint_name', default='best_ckpt.pt', type=str)
+
+    args = parser.parse_args()
+    return args
+
+
+if __name__ == '__main__':
+
+    args = get_args()
+    utils.get_device(args)
+    device = torch.device("cuda:%s" % args.gpu_ids[0]
+                          if torch.cuda.is_available() and len(args.gpu_ids)>0
+                        else "cpu")
+    args.checkpoint_dir = os.path.join(args.checkpoint_root, args.project_name)
+    os.makedirs(args.output_folder, exist_ok=True)
+
+    log_path = os.path.join(args.output_folder, 'log_vis.txt')
+
+    data_loader = utils.get_loader(args.data_name, img_size=args.img_size,
+                                   batch_size=args.batch_size,
+                                   split=args.split, is_train=False)
+
+    model = CDEvaluator(args)
+    model.load_checkpoint(args.checkpoint_name)
+    model.eval()
+
+    for i, batch in enumerate(data_loader):
+        name = batch['name']
+        print('process: %s' % name)
+        score_map = model._forward_pass(batch)
+        model._save_predictions()
+
+
+
+
+
+
+

demo.py → demo_LEVIR.py

@@ -21,10 +21,10 @@ def get_args():
     # args
     # ------------
     parser = ArgumentParser()
-    parser.add_argument('--project_name', default='BIT_LEVIR', type=str)
+    parser.add_argument('--project_name', default='ChangeFormer_LEVIR', type=str)
     parser.add_argument('--gpu_ids', type=str, default='0', help='gpu ids: e.g. 0  0,1,2, 0,2. use -1 for CPU')
     parser.add_argument('--checkpoint_root', default='checkpoints', type=str)
-    parser.add_argument('--output_folder', default='samples/predict', type=str)
+    parser.add_argument('--output_folder', default='samples_LEVIR/predict', type=str)
 
     # data
     parser.add_argument('--num_workers', default=0, type=int)
@@ -38,8 +38,8 @@ def get_args():
     # model
     parser.add_argument('--n_class', default=2, type=int)
     parser.add_argument('--embed_dim', default=256, type=int)
-    parser.add_argument('--net_G', default='ChangeFormerV5', type=str,
-                        help='base_resnet18 | base_transformer_pos_s4_dd8 | base_transformer_pos_s4_dd8_dedim8|')
+    parser.add_argument('--net_G', default='ChangeFormerV6', type=str,
+                        help='ChangeFormerV6 | base_resnet18 | base_transformer_pos_s4_dd8 | base_transformer_pos_s4_dd8_dedim8|')
     parser.add_argument('--checkpoint_name', default='best_ckpt.pt', type=str)
 
     args = parser.parse_args()