Update AV/config/config_test_general.py

AV/config/config_test_general.py

@@ -1,134 +1,137 @@
-import torch
-import os
-
-# Check GPU availability
-use_cuda = torch.cuda.is_available()
-gpu_ids = [0] if use_cuda else []
-device = torch.device('cuda' if use_cuda else 'cpu')
-
-dataset_name = 'all'  # DRIVE
-#dataset_name = 'LES'  # LES
-# dataset_name = 'hrf'  # HRF
-# dataset_name = 'ukbb'  # UKBB
-# dataset_name = 'all'
-dataset = dataset_name
-max_step = 30000  # 30000 for ukbb
-
-batch_size = 8  # default: 4
-print_iter = 100  # default: 100
-display_iter = 100  # default: 100
-save_iter = 5000  # default: 5000
-first_display_metric_iter = max_step - save_iter  # default: 25000
-lr = 0.0002  # if dataset_name!='LES' else 0.00005 # default: 0.0002
-step_size = 7000  # 7000 for DRIVE
-lr_decay_gamma = 0.5  # default: 0.5
-use_SGD = False  # default:False
-
-input_nc = 3
-ndf = 32
-netD_type = 'basic'
-n_layers_D = 5
-norm = 'instance'
-no_lsgan = False
-init_type = 'normal'
-init_gain = 0.02
-use_sigmoid = no_lsgan
-use_noise_input_D = False
-use_dropout_D = False
-# torch.cuda.set_device(gpu_ids[0])
-use_GAN = True  # default: True
-
-# adam
-beta1 = 0.5
-
-# settings for GAN loss
-num_classes_D = 1
-lambda_GAN_D = 0.01
-lambda_GAN_G = 0.01
-lambda_GAN_gp = 100
-lambda_BCE = 5
-lambda_DICE = 5
-
-input_nc_D = input_nc + 3
-
-# settings for centerness
-use_centerness = True  # default: True
-lambda_centerness = 1
-center_loss_type = 'centerness'
-centerness_map_size = [128, 128]
-
-# pretrained model
-use_pretrained_G = True
-use_pretrained_D = False
-# model_path_pretrained_G = './log/patch_pretrain'
-model_path_pretrained_G = ''
-model_step_pretrained_G = 0
-stride_height = 0
-stride_width = 0
-patch_size_list=[]
-
-def set_dataset(name):
-    global dataset_name, model_path_pretrained_G, model_step_pretrained_G
-    global stride_height, stride_width,patch_size,patch_size_list,dataset
-    dataset_name = name
-    dataset = name
-    if dataset_name == 'DRIVE':
-        model_path_pretrained_G = './AV/log/DRIVE-2023_10_20_08_36_50(6500)'
-        model_step_pretrained_G = 6500
-    elif dataset_name == 'LES':
-        model_path_pretrained_G = './AV/log/LES-2023_09_28_14_04_06(0)'
-        model_step_pretrained_G = 0
-    elif dataset_name == 'hrf':
-        model_path_pretrained_G = './AV/log/HRF-2023_10_19_11_07_31(1500)'
-        model_step_pretrained_G = 1500
-    elif dataset_name == 'ukbb':
-        model_path_pretrained_G = './AV/log/UKBB-2023_11_02_23_22_07(5000)'
-        model_step_pretrained_G = 5000
-    else:
-        model_path_pretrained_G = './AV/log/ALL-2024_09_06_09_17_18(9000)'
-        model_step_pretrained_G = 9000
-    if dataset_name == 'DRIVE':
-        patch_size_list = [64, 128, 256]
-    elif dataset_name == 'LES':
-        patch_size_list = [96, 384, 256]
-    elif dataset_name == 'hrf':
-        patch_size_list = [64, 384, 256]
-    elif dataset_name == 'ukbb':
-        patch_size_list = [96, 384, 256]
-    else:
-        patch_size_list = [96, 384, 512]
-    patch_size = patch_size_list[2]
-
-# path for dataset
-    if dataset_name == 'DRIVE' or dataset_name == 'LES' or dataset_name == 'hrf':
-        stride_height = 50
-        stride_width = 50
-    else:
-        stride_height = 150
-        stride_width = 150
-
-n_classes = 3
-
-model_step = 0
-
-# use CAM
-use_CAM = False
-
-#use resize
-use_resize = True
-resize_w_h = (1920,512)
-
-# use av_cross
-use_av_cross = False
-
-use_high_semantic = False
-lambda_high = 1  # A,V,Vessel
-
-# use global semantic
-use_global_semantic = False
-global_warmup_step = 0 if use_pretrained_G else 5000
-
-
-
-
-
+import torch
+import os
+
+# Check GPU availability
+use_cuda = torch.cuda.is_available()
+gpu_ids = [0] if use_cuda else []
+device = torch.device('cuda' if use_cuda else 'cpu')
+
+dataset_name = 'all'  # DRIVE
+#dataset_name = 'LES'  # LES
+# dataset_name = 'hrf'  # HRF
+# dataset_name = 'ukbb'  # UKBB
+# dataset_name = 'all'
+dataset = dataset_name
+max_step = 30000  # 30000 for ukbb
+
+batch_size = 8  # default: 4
+print_iter = 100  # default: 100
+display_iter = 100  # default: 100
+save_iter = 5000  # default: 5000
+first_display_metric_iter = max_step - save_iter  # default: 25000
+lr = 0.0002  # if dataset_name!='LES' else 0.00005 # default: 0.0002
+step_size = 7000  # 7000 for DRIVE
+lr_decay_gamma = 0.5  # default: 0.5
+use_SGD = False  # default:False
+
+input_nc = 3
+ndf = 32
+netD_type = 'basic'
+n_layers_D = 5
+norm = 'instance'
+no_lsgan = False
+init_type = 'normal'
+init_gain = 0.02
+use_sigmoid = no_lsgan
+use_noise_input_D = False
+use_dropout_D = False
+# torch.cuda.set_device(gpu_ids[0])
+use_GAN = True  # default: True
+
+# adam
+beta1 = 0.5
+
+# settings for GAN loss
+num_classes_D = 1
+lambda_GAN_D = 0.01
+lambda_GAN_G = 0.01
+lambda_GAN_gp = 100
+lambda_BCE = 5
+lambda_DICE = 5
+
+input_nc_D = input_nc + 3
+
+# settings for centerness
+use_centerness = True  # default: True
+lambda_centerness = 1
+center_loss_type = 'centerness'
+centerness_map_size = [128, 128]
+
+# pretrained model
+use_pretrained_G = True
+use_pretrained_D = False
+# model_path_pretrained_G = './log/patch_pretrain'
+model_path_pretrained_G = ''
+model_step_pretrained_G = 0
+stride_height = 0
+stride_width = 0
+patch_size_list=[]
+use_CAM = False
+
+#use resize
+use_resize = False
+resize_w_h = (1920,512)
+def set_dataset(name):
+    global dataset_name, model_path_pretrained_G, model_step_pretrained_G
+    global stride_height, stride_width,patch_size,patch_size_list,dataset,use_CAM,use_resize,resize_w_h
+    dataset_name = name
+    dataset = name
+    if dataset_name == 'DRIVE':
+        model_path_pretrained_G = './AV/log/DRIVE-2023_10_20_08_36_50(6500)'
+        model_step_pretrained_G = 6500
+    elif dataset_name == 'LES':
+        model_path_pretrained_G = './AV/log/LES-2023_09_28_14_04_06(0)'
+        model_step_pretrained_G = 0
+    elif dataset_name == 'hrf':
+        model_path_pretrained_G = './AV/log/HRF-2023_10_19_11_07_31(1500)'
+        model_step_pretrained_G = 1500
+    elif dataset_name == 'ukbb':
+        model_path_pretrained_G = './AV/log/UKBB-2023_11_02_23_22_07(5000)'
+        model_step_pretrained_G = 5000
+    else:
+        model_path_pretrained_G = './AV/log/ALL-2024_09_06_09_17_18(9000)'
+        model_step_pretrained_G = 9000
+    if dataset_name == 'DRIVE':
+        patch_size_list = [64, 128, 256]
+    elif dataset_name == 'LES':
+        patch_size_list = [96, 384, 256]
+    elif dataset_name == 'hrf':
+        patch_size_list = [64, 384, 256]
+    elif dataset_name == 'ukbb':
+        patch_size_list = [96, 384, 256]
+    else:
+        patch_size_list = [96, 384, 512]
+    patch_size = patch_size_list[2]
+
+# path for dataset
+    if dataset_name == 'DRIVE' or dataset_name == 'LES' or dataset_name == 'hrf':
+        stride_height = 50
+        stride_width = 50
+    elif dataset_name == 'ukbb':
+        stride_height = 150
+        stride_width = 150
+    else:
+        use_CAM=True
+        stride_height = 150
+        stride_width = 150
+        
+
+n_classes = 3
+
+model_step = 0
+
+
+# use av_cross
+use_av_cross = False
+
+use_high_semantic = False
+lambda_high = 1  # A,V,Vessel
+
+# use global semantic
+use_global_semantic = False
+global_warmup_step = 0 if use_pretrained_G else 5000
+
+
+
+
+