Adapt to new version

hyperlpr/pipline.py

@@ -185,7 +185,7 @@ def SimpleRecognizePlateByE2E(image):
         image_rgb = fv.finemappingVertical(image_rgb)
         image_rgb = fv.finemappingVertical(image_rgb)
         cache.verticalMappingToFolder(image_rgb)
-        cv2.imwrite("./"+str(j)+".jpg",image_rgb)
+        #cv2.imwrite("./"+str(j)+".jpg",image_rgb)
         res,confidence = e2e.recognizeOne(image_rgb)
         print res,confidence
         res_set.append([[],res,confidence])

hyperlpr/recognizer.py

@@ -5,7 +5,7 @@ from keras.layers import Conv2D,MaxPool2D
 from keras.optimizers import SGD
 from keras import backend as K
 
-K.set_image_dim_ordering('tf')
+K.image_data_format()
 
 
 import cv2

hyperlpr/segmentation.py

@@ -19,7 +19,7 @@ from keras.layers import Conv2D, MaxPool2D
 from keras.optimizers import SGD
 from keras import backend as K
 
-K.set_image_dim_ordering('tf')
+K.image_data_format()
 
 
 def Getmodel_tensorflow(nb_classes):

hyperlpr/typeDistinguish.py

@@ -5,7 +5,7 @@ from keras.layers import Conv2D, MaxPool2D
 from keras.optimizers import SGD
 from keras import backend as K
 
-K.set_image_dim_ordering('tf')
+K.image_data_format()
 
 
 import cv2