fix bugs

extract_feature.py

@@ -97,7 +97,7 @@ def main(_):
 
         print 'extract traning feature'
 
-        data_files = glob(os.path.join("./data", 'uc_train_256_feat', "*.jpg"))
+        data_files = glob(os.path.join("./data", 'uc_train_256_data', "*.jpg"))
         shuffle(data_files)
 
 
@@ -129,7 +129,7 @@ def main(_):
             begin = FLAGS.batch_size*idx
             end = FLAGS.batch_size + begin
             feats[begin:end, ...] = feat 
-
+            print idx
         np.save('features/features%d_train.npy'%num, feats)
         np.save('features/label%d_train.npy'%num, y)
 
@@ -167,7 +167,7 @@ def main(_):
             end = FLAGS.batch_size + begin
             feats[begin:end, ...] = feat 
 
-            #print idx
+            print idx
 
         np.save('features/features%d_test.npy'%num, feats)
         np.save('features/label%d_test.npy'%num, y)

features/.gitignore

@@ -0,0 +1,2 @@
+*
+!.gitignore

network.py

@@ -19,7 +19,7 @@
 
 def generator_simplified_api(inputs, is_train=True, reuse=False):
     image_size = 256
-    k = 5
+    k = 4
     # 128, 64, 32, 16
     s2, s4, s8, s16, s32, s64 = int(image_size/2), int(image_size/4), int(image_size/8), int(image_size/16), int(image_size/32), int(image_size/64)
 

style_names.txt

@@ -0,0 +1,21 @@
+mobilehomepark
+beach
+tenniscourt
+airplane
+denseresidential
+harbor
+buildings
+forest
+intersection
+river
+sparseresidential
+runway
+parkinglot
+baseballdiamond
+agricultural
+storagetanks
+chaparral
+golfcourse
+freeway
+mediumresidential
+overpass

train_marta_gan.py

@@ -179,7 +179,7 @@ def main(_):
                 print("[Sample] d_loss: %.8f, g_loss: %.8f" % (errD, errG))
 #                for i in range(len(D)):
 #                    print D[i].shape
-                print D[-1], D_, sigmoid(D[-1]), sigmoid(D[-1])==D_
+                #print D[-1], D_, sigmoid(D[-1]), sigmoid(D[-1])==D_
                 sys.stdout.flush()
 
             if np.mod(epoch, 5) == 0:

train_svm.py

@@ -16,12 +16,12 @@
 #
 import numpy as np
 acc = []
-nums = [55, 60, 65, 70, 75, 80, 85]
+nums = [75]
 for num in nums:
-    X_train=np.load('feat_match/features%d_train.npy'%num)
-    y_train=np.load('feat_match/label%d_train.npy'%num)
-    X_test=np.load('feat_match/features%d_test.npy'%num)
-    y_test=np.load('feat_match/label%d_test.npy'%num)
+    X_train=np.load('features/features%d_train.npy'%num)
+    y_train=np.load('features/label%d_train.npy'%num)
+    X_test=np.load('features/features%d_test.npy'%num)
+    y_test=np.load('features/label%d_test.npy'%num)
 
     print("Fitting the classifier to the training set")
     t0 = time()