cmt-20230409-2: some fixs

cnn_gray/resize_filter/cross_validation/new2/cnn_train1.py

@@ -15,8 +15,8 @@
 
 model_path = "model/model.ckpt"
 
-data0 = np.genfromtxt("train_set_new/training data.txt")
-label = np.genfromtxt("train_set_new/labels.txt")
+data0 = np.genfromtxt("train_set/training data.txt")
+label = np.genfromtxt("train_set/labels.txt")
 data = []
 for i in range(data0.shape[0]):
     data_tmp = data0[i,:]

cnn_gray/resize_filter/cross_validation/new2/getTrainingAbnormal.py

@@ -1,7 +1,7 @@
 import numpy as np
 
-data = np.genfromtxt("train_set_new/training data.txt")
-label = np.genfromtxt("train_set_new/labels.txt")
+data = np.genfromtxt("train_set/training data.txt")
+label = np.genfromtxt("train_set/labels.txt")
 
 print(data.shape)
 print(label.shape)

cnn_gray/resize_filter/cross_validation/new2/get_validation.py

@@ -54,5 +54,5 @@
         count = count + 1
 print(count)
 
-np.savetxt("train_set_new/training data.txt", data_new)
-np.savetxt("train_set_new/labels.txt", label_new)
+np.savetxt("train_set/training data.txt", data_new)
+np.savetxt("train_set/labels.txt", label_new)

cnn_gray/resize_filter/cross_validation/new22/cnn_train1.py

@@ -15,8 +15,8 @@
 
 model_path = "model/model.ckpt"
 
-data0 = np.genfromtxt("train_set_new/training data.txt")
-label = np.genfromtxt("train_set_new/labels.txt")
+data0 = np.genfromtxt("train_set/training data.txt")
+label = np.genfromtxt("train_set/labels.txt")
 data = []
 for i in range(data0.shape[0]):
     data_tmp = data0[i,:]

cnn_gray/resize_filter/cross_validation/new22/getTrainingAbnormal.py

@@ -1,7 +1,7 @@
 import numpy as np
 
-data = np.genfromtxt("train_set_new/training data.txt")
-label = np.genfromtxt("train_set_new/labels.txt")
+data = np.genfromtxt("train_set/training data.txt")
+label = np.genfromtxt("train_set/labels.txt")
 
 print(data.shape)
 print(label.shape)

cnn_gray/resize_filter/cross_validation/new22/get_validation.py

@@ -57,5 +57,5 @@
         count = count + 1
 print(count)
 
-np.savetxt("train_set_new/training data.txt", data_new)
-np.savetxt("train_set_new/labels.txt", label_new)
+np.savetxt("train_set/training data.txt", data_new)
+np.savetxt("train_set/labels.txt", label_new)

cnn_gray/resize_filter/cross_validation/new32/cnn_train1.py

@@ -15,8 +15,8 @@
 
 model_path = "model/model.ckpt"
 
-data0 = np.genfromtxt("train_set_new/training data.txt")
-label = np.genfromtxt("train_set_new/labels.txt")
+data0 = np.genfromtxt("train_set/training data.txt")
+label = np.genfromtxt("train_set/labels.txt")
 data = []
 for i in range(data0.shape[0]):
     data_tmp = data0[i,:]

cnn_gray/resize_filter/cross_validation/new32/getTrainingAbnormal.py

@@ -1,7 +1,7 @@
 import numpy as np
 
-data = np.genfromtxt("train_set_new/training data.txt")
-label = np.genfromtxt("train_set_new/labels.txt")
+data = np.genfromtxt("train_set/training data.txt")
+label = np.genfromtxt("train_set/labels.txt")
 
 print(data.shape)
 print(label.shape)

cnn_gray/resize_filter/cross_validation/new32/get_validation.py

@@ -54,5 +54,5 @@
         count = count + 1
 print(count)
 
-np.savetxt("train_set_new/training data.txt", data_new)
-np.savetxt("train_set_new/labels.txt", label_new)
+np.savetxt("train_set/training data.txt", data_new)
+np.savetxt("train_set/labels.txt", label_new)

cnn_gray/resize_filter/cross_validation/new42/cnn_train1.py

@@ -15,8 +15,8 @@
 
 model_path = "model/model.ckpt"
 
-data0 = np.genfromtxt("train_set_new/training data.txt")
-label = np.genfromtxt("train_set_new/labels.txt")
+data0 = np.genfromtxt("train_set/training data.txt")
+label = np.genfromtxt("train_set/labels.txt")
 data = []
 for i in range(data0.shape[0]):
     data_tmp = data0[i,:]

cnn_gray/resize_filter/cross_validation/new42/getTrainingAbnormal.py

@@ -1,7 +1,7 @@
 import numpy as np
 
-data = np.genfromtxt("train_set_new/training data.txt")
-label = np.genfromtxt("train_set_new/labels.txt")
+data = np.genfromtxt("train_set/training data.txt")
+label = np.genfromtxt("train_set/labels.txt")
 
 print(data.shape)
 print(label.shape)

cnn_gray/resize_filter/cross_validation/new42/get_validation.py

@@ -54,5 +54,5 @@
         count = count + 1
 print(count)
 
-np.savetxt("train_set_new/training data.txt", data_new)
-np.savetxt("train_set_new/labels.txt", label_new)
+np.savetxt("train_set/training data.txt", data_new)
+np.savetxt("train_set/labels.txt", label_new)

cnn_gray/resize_filter1/cross_validation/new2/cnn_train1.py

@@ -15,8 +15,8 @@
 
 model_path = "model/model.ckpt"
 
-data0 = np.genfromtxt("train_set_new/training data.txt")
-label = np.genfromtxt("train_set_new/labels.txt")
+data0 = np.genfromtxt("train_set/training data.txt")
+label = np.genfromtxt("train_set/labels.txt")
 data = []
 for i in range(data0.shape[0]):
     data_tmp = data0[i,:]

cnn_gray/resize_filter1/cross_validation/new2/getTrainingAbnormal.py

@@ -1,7 +1,7 @@
 import numpy as np
 
-data = np.genfromtxt("train_set_new/training data.txt")
-label = np.genfromtxt("train_set_new/labels.txt")
+data = np.genfromtxt("train_set/training data.txt")
+label = np.genfromtxt("train_set/labels.txt")
 
 print(data.shape)
 print(label.shape)

cnn_gray/resize_filter1/cross_validation/new2/get_validation.py

@@ -54,5 +54,5 @@
         count = count + 1
 print(count)
 
-np.savetxt("train_set_new/training data.txt", data_new)
-np.savetxt("train_set_new/labels.txt", label_new)
+np.savetxt("train_set/training data.txt", data_new)
+np.savetxt("train_set/labels.txt", label_new)

cnn_gray/resize_filter1/cross_validation/new22/cnn_train1.py

@@ -15,8 +15,8 @@
 
 model_path = "model/model.ckpt"
 
-data0 = np.genfromtxt("train_set_new/training data.txt")
-label = np.genfromtxt("train_set_new/labels.txt")
+data0 = np.genfromtxt("train_set/training data.txt")
+label = np.genfromtxt("train_set/labels.txt")
 data = []
 for i in range(data0.shape[0]):
     data_tmp = data0[i,:]

cnn_gray/resize_filter1/cross_validation/new22/getTrainingAbnormal.py

@@ -1,7 +1,7 @@
 import numpy as np
 
-data = np.genfromtxt("train_set_new/training data.txt")
-label = np.genfromtxt("train_set_new/labels.txt")
+data = np.genfromtxt("train_set/training data.txt")
+label = np.genfromtxt("train_set/labels.txt")
 
 print(data.shape)
 print(label.shape)

cnn_gray/resize_filter1/cross_validation/new22/get_validation.py

@@ -57,5 +57,5 @@
         count = count + 1
 print(count)
 
-np.savetxt("train_set_new/training data.txt", data_new)
-np.savetxt("train_set_new/labels.txt", label_new)
+np.savetxt("train_set/training data.txt", data_new)
+np.savetxt("train_set/labels.txt", label_new)

cnn_gray/resize_filter1/cross_validation/new32/cnn_train1.py

@@ -15,8 +15,8 @@
 
 model_path = "model/model.ckpt"
 
-data0 = np.genfromtxt("train_set_new/training data.txt")
-label = np.genfromtxt("train_set_new/labels.txt")
+data0 = np.genfromtxt("train_set/training data.txt")
+label = np.genfromtxt("train_set/labels.txt")
 data = []
 for i in range(data0.shape[0]):
     data_tmp = data0[i,:]

cnn_gray/resize_filter1/cross_validation/new32/getTrainingAbnormal.py

@@ -1,7 +1,7 @@
 import numpy as np
 
-data = np.genfromtxt("train_set_new/training data.txt")
-label = np.genfromtxt("train_set_new/labels.txt")
+data = np.genfromtxt("train_set/training data.txt")
+label = np.genfromtxt("train_set/labels.txt")
 
 print(data.shape)
 print(label.shape)

cnn_gray/resize_filter1/cross_validation/new32/get_validation.py

@@ -54,5 +54,5 @@
         count = count + 1
 print(count)
 
-np.savetxt("train_set_new/training data.txt", data_new)
-np.savetxt("train_set_new/labels.txt", label_new)
+np.savetxt("train_set/training data.txt", data_new)
+np.savetxt("train_set/labels.txt", label_new)

cnn_gray/resize_filter1/cross_validation/new42/cnn_train1.py

@@ -15,8 +15,8 @@
 
 model_path = "model/model.ckpt"
 
-data0 = np.genfromtxt("train_set_new/training data.txt")
-label = np.genfromtxt("train_set_new/labels.txt")
+data0 = np.genfromtxt("train_set/training data.txt")
+label = np.genfromtxt("train_set/labels.txt")
 data = []
 for i in range(data0.shape[0]):
     data_tmp = data0[i,:]

cnn_gray/resize_filter1/cross_validation/new42/getTrainingAbnormal.py

@@ -1,7 +1,7 @@
 import numpy as np
 
-data = np.genfromtxt("train_set_new/training data.txt")
-label = np.genfromtxt("train_set_new/labels.txt")
+data = np.genfromtxt("train_set/training data.txt")
+label = np.genfromtxt("train_set/labels.txt")
 
 print(data.shape)
 print(label.shape)

cnn_gray/resize_filter1/cross_validation/new42/get_validation.py

@@ -54,5 +54,5 @@
         count = count + 1
 print(count)
 
-np.savetxt("train_set_new/training data.txt", data_new)
-np.savetxt("train_set_new/labels.txt", label_new)
+np.savetxt("train_set/training data.txt", data_new)
+np.savetxt("train_set/labels.txt", label_new)

data_augmentation/data_augmentation_1.py

@@ -1,9 +1,9 @@
 # -*- coding: utf-8 -*-
 import numpy as np
 
-data = np.genfromtxt("train_set_new/training data.txt")
+data = np.genfromtxt("train_set/training data.txt")
 # print(data.shape)
-labels = np.genfromtxt("train_set_new/labels.txt")
+labels = np.genfromtxt("train_set/labels.txt")
 
 data_origin = []
 data_flip_a = []
@@ -121,5 +121,5 @@
 #     if labels_new[i] == 1:
 #         abnormal_count_new = abnormal_count_new + 1
 # print(abnormal_count_new)
-np.savetxt("train_set_new/training data.txt", data_new)
-np.savetxt("train_set_new/labels.txt", labels_new)
+np.savetxt("train_set/training data.txt", data_new)
+np.savetxt("train_set/labels.txt", labels_new)

rnn_gray/SignalDataSet.py

@@ -27,7 +27,7 @@ def getDataLabel(path):
     return data, label
 
 # validation
-# path = 'train_set_new/'
+# path = 'train_set/'
 # data, label = getDataLabel(path)
 # print(data.shape)
 # print(label.shape)

rnn_gray/rnn_test.py

@@ -25,7 +25,7 @@ def get_dataset(path):
     label = label[order]
     return data, label
 
-test_data, test_target = get_dataset('test_set_new/')
+test_data, test_target = get_dataset('test_set/')
 print(test_data.shape)
 print(test_target.shape)
 

rnn_gray/rnn_train.py

@@ -20,7 +20,7 @@
 
 def get_dataset(path):
     # Flatten images into vectors.
-    # path = 'train_set_new/'
+    # path = 'train_set/'
     data,label = getDataLabel(path)
     data = data.reshape(data.shape[:2] + (-1,))
     # One-hot encode labels.
@@ -42,10 +42,10 @@ def get_dataset(path):
 
 
 # Split into training and test data.
-train_data, train_target = get_dataset('train_set_new/')
+train_data, train_target = get_dataset('train_set/')
 print(train_data.shape)
 print(train_target.shape)
-test_data, test_target = get_dataset('test_set_new/')
+test_data, test_target = get_dataset('test_set/')
 print(test_data.shape)
 print(test_target.shape)
 abnormal_data = []

rnn_gray/rnn_train_bidirectional.py

@@ -21,7 +21,7 @@
 
 def get_dataset(path):
     # Flatten images into vectors.
-    # path = 'train_set_new/'
+    # path = 'train_set/'
     data,label = getDataLabel(path)
     data = data.reshape(data.shape[:2] + (-1,))
     # One-hot encode labels.
@@ -42,10 +42,10 @@ def get_dataset(path):
     return data, label
 
 # Split into training and test data.
-train_data, train_target = get_dataset('train_set_new/')
+train_data, train_target = get_dataset('train_set/')
 print(train_data.shape)
 print(train_target.shape)
-test_data, test_target = get_dataset('test_set_new/')
+test_data, test_target = get_dataset('test_set/')
 print(test_data.shape)
 print(test_target.shape)
 abnormal_data = []