diff --git a/.gitattributes b/.gitattributes
index 55cab133643a2a73e083373d2106533678d0edd5..6c1210240671080ded186eca822d5f2e012d6b09 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -56,3 +56,12 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+CHASEDB1/images/01_test.tif filter=lfs diff=lfs merge=lfs -text
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+CHASEDB1/images/14_test.tif filter=lfs diff=lfs merge=lfs -text
+CHASEDB1/images/19_test.tif filter=lfs diff=lfs merge=lfs -text
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+++ b/chasedb1.py
@@ -0,0 +1,46 @@
+import os
+from os.path import join
+
+def get_path_list(root_path,img_path,label_path,fov_path):
+    tmp_list = [img_path,label_path,fov_path]
+    res = []
+    for i in range(len(tmp_list)):
+        data_path = join(data_root_path,tmp_list[i])
+        filename_list = os.listdir(data_path)
+        filename_list.sort()
+        res.append([join(data_path,j) for j in filename_list])
+    return res
+
+def write_path_list(name_list, save_path, file_name):
+    f = open(join(save_path, file_name), 'w')
+    for i in range(len(name_list[0])):
+        f.write(str(name_list[0][i]) + " " + str(name_list[1][i]) + " " + str(name_list[2][i]) + '\n')
+    f.close()
+
+if __name__ == "__main__":
+    #------------Path of the dataset --------------------------------
+    data_root_path = ''
+    # if not os.path.exists(data_root_path): raise ValueError("data path is not exist, Please make sure your data path is correct")
+    #train
+    img = "CHASEDB1/images"
+    gt = "CHASEDB1/1st_label"
+    fov = "CHASEDB1/mask"
+    #---------------save path-----------------------------------------
+    save_path = "./data_path_list/CHASEDB1"
+    if not os.path.exists(save_path):
+        os.mkdir(save_path)
+    #-----------------------------------------------------------------
+    data_list = get_path_list(data_root_path,img,gt,fov)
+    print('Numbers of all imgs:',len(data_list[0]))
+    test_range = (0,7) # 测试集索引范围，左闭右开
+    train_list = [data_list[i][:test_range[0]] + data_list[i][test_range[1]:] for i in range(len(data_list))]
+    test_list = [data_list[i][test_range[0]:test_range[1]] for i in range(len(data_list))]
+
+    print('Number of train imgs:',len(train_list[0]))
+    write_path_list(train_list, save_path, 'train.txt')
+
+    print('Number of test imgs:',len(test_list[0]))
+    write_path_list(test_list, save_path, 'test.txt')
+
+    print("Finish!")
+    
diff --git a/data_path_list/.gitignore b/data_path_list/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..f218ac4f6db114c5918cf911bb551c1f0b5a2359
--- /dev/null
+++ b/data_path_list/.gitignore
@@ -0,0 +1,4 @@
+# ignore path list files of datasets
+DRIVE/
+CHASEDB1/
+STARE/
diff --git a/data_path_list/CHASEDB1/test.txt b/data_path_list/CHASEDB1/test.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7280662699501adbf242f919508caa84e4004e87
--- /dev/null
+++ b/data_path_list/CHASEDB1/test.txt
@@ -0,0 +1,7 @@
+CHASEDB1/images\01_test.tif CHASEDB1/1st_label\01_manual1.tif CHASEDB1/mask\mask_01L.png
+CHASEDB1/images\02_test.tif CHASEDB1/1st_label\02_manual1.tif CHASEDB1/mask\mask_01R.png
+CHASEDB1/images\03_test.tif CHASEDB1/1st_label\03_manual1.tif CHASEDB1/mask\mask_02L.png
+CHASEDB1/images\04_test.tif CHASEDB1/1st_label\04_manual1.tif CHASEDB1/mask\mask_02R.png
+CHASEDB1/images\05_test.tif CHASEDB1/1st_label\05_manual1.tif CHASEDB1/mask\mask_03L.png
+CHASEDB1/images\06_test.tif CHASEDB1/1st_label\06_manual1.tif CHASEDB1/mask\mask_03R.png
+CHASEDB1/images\07_test.tif CHASEDB1/1st_label\07_manual1.tif CHASEDB1/mask\mask_04L.png
diff --git a/data_path_list/CHASEDB1/train.txt b/data_path_list/CHASEDB1/train.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7c32e350595a2cba99272ae4a9fbebdab6f4c625
--- /dev/null
+++ b/data_path_list/CHASEDB1/train.txt
@@ -0,0 +1,13 @@
+CHASEDB1/images\08_test.tif CHASEDB1/1st_label\08_manual1.tif CHASEDB1/mask\mask_04R.png
+CHASEDB1/images\09_test.tif CHASEDB1/1st_label\09_manual1.tif CHASEDB1/mask\mask_05L.png
+CHASEDB1/images\10_test.tif CHASEDB1/1st_label\10_manual1.tif CHASEDB1/mask\mask_05R.png
+CHASEDB1/images\11_test.tif CHASEDB1/1st_label\11_manual1.tif CHASEDB1/mask\mask_06L.png
+CHASEDB1/images\12_test.tif CHASEDB1/1st_label\12_manual1.tif CHASEDB1/mask\mask_06R.png
+CHASEDB1/images\13_test.tif CHASEDB1/1st_label\13_manual1.tif CHASEDB1/mask\mask_07L.png
+CHASEDB1/images\14_test.tif CHASEDB1/1st_label\14_manual1.tif CHASEDB1/mask\mask_07R.png
+CHASEDB1/images\15_test.tif CHASEDB1/1st_label\15_manual1.tif CHASEDB1/mask\mask_08L.png
+CHASEDB1/images\16_test.tif CHASEDB1/1st_label\16_manual1.tif CHASEDB1/mask\mask_08R.png
+CHASEDB1/images\17_test.tif CHASEDB1/1st_label\17_manual1.tif CHASEDB1/mask\mask_09L.png
+CHASEDB1/images\18_test.tif CHASEDB1/1st_label\18_manual1.tif CHASEDB1/mask\mask_09R.png
+CHASEDB1/images\19_test.tif CHASEDB1/1st_label\19_manual1.tif CHASEDB1/mask\mask_10L.png
+CHASEDB1/images\20_test.tif CHASEDB1/1st_label\20_manual1.tif CHASEDB1/mask\mask_10R.png
diff --git a/data_path_list/DRIVE/test.txt b/data_path_list/DRIVE/test.txt
new file mode 100644
index 0000000000000000000000000000000000000000..0bbc042cb3e2b020264c0fa86e19ebcee9656a9d
--- /dev/null
+++ b/data_path_list/DRIVE/test.txt
@@ -0,0 +1,10 @@
+DRIVE/test/images/31_training.tif DRIVE/test/1st_manual/31_manual1.gif DRIVE/test/mask/31_training_mask.gif
+DRIVE/test/images/32_training.tif DRIVE/test/1st_manual/32_manual1.gif DRIVE/test/mask/32_training_mask.gif
+DRIVE/test/images/33_training.tif DRIVE/test/1st_manual/33_manual1.gif DRIVE/test/mask/33_training_mask.gif
+DRIVE/test/images/34_training.tif DRIVE/test/1st_manual/34_manual1.gif DRIVE/test/mask/34_training_mask.gif
+DRIVE/test/images/35_training.tif DRIVE/test/1st_manual/35_manual1.gif DRIVE/test/mask/35_training_mask.gif
+DRIVE/test/images/36_training.tif DRIVE/test/1st_manual/36_manual1.gif DRIVE/test/mask/36_training_mask.gif
+DRIVE/test/images/37_training.tif DRIVE/test/1st_manual/37_manual1.gif DRIVE/test/mask/37_training_mask.gif
+DRIVE/test/images/38_training.tif DRIVE/test/1st_manual/38_manual1.gif DRIVE/test/mask/38_training_mask.gif
+DRIVE/test/images/39_training.tif DRIVE/test/1st_manual/39_manual1.gif DRIVE/test/mask/39_training_mask.gif
+DRIVE/test/images/40_training.tif DRIVE/test/1st_manual/40_manual1.gif DRIVE/test/mask/40_training_mask.gif
diff --git a/data_path_list/DRIVE/train.txt b/data_path_list/DRIVE/train.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3e1bd8db2bee1d6a6c9e97a8e8bb0837a4efe563
--- /dev/null
+++ b/data_path_list/DRIVE/train.txt
@@ -0,0 +1,10 @@
+DRIVE/training/images/21_training.tif DRIVE/training/1st_manual/21_manual1.gif DRIVE/training/mask/21_training_mask.gif
+DRIVE/training/images/22_training.tif DRIVE/training/1st_manual/22_manual1.gif DRIVE/training/mask/22_training_mask.gif
+DRIVE/training/images/23_training.tif DRIVE/training/1st_manual/23_manual1.gif DRIVE/training/mask/23_training_mask.gif
+DRIVE/training/images/24_training.tif DRIVE/training/1st_manual/24_manual1.gif DRIVE/training/mask/24_training_mask.gif
+DRIVE/training/images/25_training.tif DRIVE/training/1st_manual/25_manual1.gif DRIVE/training/mask/25_training_mask.gif
+DRIVE/training/images/26_training.tif DRIVE/training/1st_manual/26_manual1.gif DRIVE/training/mask/26_training_mask.gif
+DRIVE/training/images/27_training.tif DRIVE/training/1st_manual/27_manual1.gif DRIVE/training/mask/27_training_mask.gif
+DRIVE/training/images/28_training.tif DRIVE/training/1st_manual/28_manual1.gif DRIVE/training/mask/28_training_mask.gif
+DRIVE/training/images/29_training.tif DRIVE/training/1st_manual/29_manual1.gif DRIVE/training/mask/29_training_mask.gif
+DRIVE/training/images/30_training.tif DRIVE/training/1st_manual/30_manual1.gif DRIVE/training/mask/30_training_mask.gif
diff --git a/data_path_list/STARE/test.txt b/data_path_list/STARE/test.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f21153a4e242398a12bf15a0428b2c9b84c956e1
--- /dev/null
+++ b/data_path_list/STARE/test.txt
@@ -0,0 +1,5 @@
+C:\Users\gowth\Downloads\Modified_LadderNet_Densenet_VesselSeg\prepare_dataset\STARE/images/im0001.png C:\Users\gowth\Downloads\Modified_LadderNet_Densenet_VesselSeg\prepare_dataset\STARE/masks_ah/im0001.png C:\Users\gowth\Downloads\Modified_LadderNet_Densenet_VesselSeg\prepare_dataset\STARE/masks_vk/im0001.png
+C:\Users\gowth\Downloads\Modified_LadderNet_Densenet_VesselSeg\prepare_dataset\STARE/images/im0002.png C:\Users\gowth\Downloads\Modified_LadderNet_Densenet_VesselSeg\prepare_dataset\STARE/masks_ah/im0001_2ndHO.png C:\Users\gowth\Downloads\Modified_LadderNet_Densenet_VesselSeg\prepare_dataset\STARE/masks_vk/im0001_1stHO.png
+C:\Users\gowth\Downloads\Modified_LadderNet_Densenet_VesselSeg\prepare_dataset\STARE/images/im0003.png C:\Users\gowth\Downloads\Modified_LadderNet_Densenet_VesselSeg\prepare_dataset\STARE/masks_ah/im0002.png C:\Users\gowth\Downloads\Modified_LadderNet_Densenet_VesselSeg\prepare_dataset\STARE/masks_vk/im0002.png
+C:\Users\gowth\Downloads\Modified_LadderNet_Densenet_VesselSeg\prepare_dataset\STARE/images/im0004.png C:\Users\gowth\Downloads\Modified_LadderNet_Densenet_VesselSeg\prepare_dataset\STARE/masks_ah/im0002_2ndHO.png C:\Users\gowth\Downloads\Modified_LadderNet_Densenet_VesselSeg\prepare_dataset\STARE/masks_vk/im0002_1stHO.png
+C:\Users\gowth\Downloads\Modified_LadderNet_Densenet_VesselSeg\prepare_dataset\STARE/images/im0005.png C:\Users\gowth\Downloads\Modified_LadderNet_Densenet_VesselSeg\prepare_dataset\STARE/masks_ah/im0003.png C:\Users\gowth\Downloads\Modified_LadderNet_Densenet_VesselSeg\prepare_dataset\STARE/masks_vk/im0003.png
diff --git a/data_path_list/STARE/train.txt b/data_path_list/STARE/train.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f2155725faf745d3af23867210712c3d5aa11eda
--- /dev/null
+++ b/data_path_list/STARE/train.txt
@@ -0,0 +1,15 @@
+C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\images\im0044.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_ah\im0003_2ndHO.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_vk\im0003_1stHO.png
+C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\images\im0077.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_ah\im0004.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_vk\im0004.png
+C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\images\im0081.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_ah\im0004_2ndHO.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_vk\im0004_1stHO.png
+C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\images\im0082.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_ah\im0005.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_vk\im0005.png
+C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\images\im0139.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_ah\im0005_2ndHO.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_vk\im0005_1stHO.png
+C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\images\im0162.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_ah\im0044.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_vk\im0044.png
+C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\images\im0163.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_ah\im0044_2ndHO.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_vk\im0044_1stHO.png
+C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\images\im0235.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_ah\im0077.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_vk\im0077.png
+C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\images\im0236.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_ah\im0077_2ndHO.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_vk\im0077_1stHO.png
+C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\images\im0239.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_ah\im0081.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_vk\im0081.png
+C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\images\im0240.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_ah\im0081_2ndHO.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_vk\im0081_1stHO.png
+C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\images\im0255.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_ah\im0082.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_vk\im0082.png
+C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\images\im0291.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_ah\im0082_2ndHO.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_vk\im0082_1stHO.png
+C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\images\im0319.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_ah\im0139.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_vk\im0139.png
+C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\images\im0324.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_ah\im0139_2ndHO.png C:\Users\gowth\Downloads\VesselSeg-Pytorch\Modified_LadderNet_Densenet_VesselSeg\STARE\masks_vk\im0139_1stHO.png
diff --git a/drive.py b/drive.py
new file mode 100644
index 0000000000000000000000000000000000000000..4449103f5aa0b072d5c43a1a0f86a82736c35fc2
--- /dev/null
+++ b/drive.py
@@ -0,0 +1,49 @@
+import os
+import h5py,cv2,imageio
+import numpy as np
+from PIL import Image
+from os.path import join
+
+def get_path_list(root_path,img_path,label_path,fov_path):
+    tmp_list = [img_path,label_path,fov_path]
+    res = []
+    for i in range(len(tmp_list)):
+        data_path = join(data_root_path,tmp_list[i])
+        filename_list = os.listdir(data_path)
+        filename_list.sort()
+        res.append([join(data_path,j) for j in filename_list])
+    return res
+
+def write_path_list(name_list, save_path, file_name):
+    f = open(join(save_path, file_name), 'w')
+    for i in range(len(name_list[0])):
+        f.write(str(name_list[0][i]) + " " + str(name_list[1][i]) + " " + str(name_list[2][i]) + '\n')
+    f.close()
+
+if __name__ == "__main__":
+    #------------Path of the dataset -------------------------
+    data_root_path = ''
+    # if not os.path.exists(data_root_path): raise ValueError("data path is not exist, Please make sure your data path is correct")
+    #train
+    img_train = "DRIVE/training/images/"
+    gt_train = "DRIVE/training/1st_manual/"
+    fov_train = "DRIVE/training/mask/"
+    #test
+    img_test = "DRIVE/test/images/"
+    gt_test = "DRIVE/test/1st_manual/"
+    fov_test = "DRIVE/test/mask/"
+
+    save_path = "./data_path_list/DRIVE/"
+    if not os.path.isdir(save_path):
+        os.mkdir(save_path)
+
+    train_list = get_path_list(data_root_path,img_train,gt_train,fov_train)
+    print('Number of train imgs:',len(train_list[0]))
+    write_path_list(train_list, save_path, 'train.txt')
+
+    test_list = get_path_list(data_root_path,img_test,gt_test,fov_test)
+    print('Number of test imgs:',len(test_list[0]))
+    write_path_list(test_list, save_path, 'test.txt')
+
+    print("Finish!")
+    
diff --git a/stare.py b/stare.py
new file mode 100644
index 0000000000000000000000000000000000000000..f9d9d435e94a3420d62048901b8c7fb33fb8137e
--- /dev/null
+++ b/stare.py
@@ -0,0 +1,46 @@
+import os
+from os.path import join
+
+def get_path_list(root_path,img_path,label_path,fov_path):
+    tmp_list = [img_path,label_path,fov_path]
+    res = []
+    for i in range(len(tmp_list)):
+        data_path = join(data_root_path,tmp_list[i])
+        filename_list = os.listdir(data_path)
+        filename_list.sort()
+        res.append([join(data_path,j) for j in filename_list])
+    return res
+
+def write_path_list(name_list, save_path, file_name):
+    f = open(join(save_path, file_name), 'w')
+    for i in range(len(name_list[0])):
+        f.write(str(name_list[0][i]) + " " + str(name_list[1][i]) + " " + str(name_list[2][i]) + '\n')
+    f.close()
+
+if __name__ == "__main__":
+  
+    data_root_path = ''
+    # if not os.path.exists(data_root_path): raise ValueError("data path is not exist, Please make sure your data path is correct")
+    #train
+    img = "STARE/images"
+    gt = "STARE/masks_ah"
+    fov = "STARE/masks_vk"
+
+    save_path = "./data_path_list/STARE"
+    if not os.path.exists(save_path):
+        os.mkdir(save_path)
+
+    data_list = get_path_list(data_root_path,img,gt,fov)
+    print('Numbers of all imgs:',len(data_list[0]))
+    test_range = (0,5) 
+    train_list = [data_list[i][:test_range[0]] + data_list[i][test_range[1]:] for i in range(len(data_list))]
+    test_list = [data_list[i][test_range[0]:test_range[1]] for i in range(len(data_list))]
+
+    print('Number of train imgs:',len(train_list[0]))
+    write_path_list(train_list, save_path, 'train.txt')
+
+    print('Number of test imgs:',len(test_list[0]))
+    write_path_list(test_list, save_path, 'test.txt')
+
+    print("Finish!")
+