orgnize folder

Author: foamliu

.gitignore

@@ -5,7 +5,7 @@ cars_test.tgz
 cars_train.tgz
 custom_layers/__pycache__/
 data/
-imagenet_models/
+models/
 logs/
 cars_test/
 cars_train/

clean.sh

@@ -3,4 +3,4 @@ rm logs/ -r
 rm cars_test/ -r
 rm cars_train/ -r
 rm devkit/ -r
-rm training.log
+rm training.log

pre-process.py

@@ -169,4 +169,4 @@ def process_test_data():
     # clean up
     shutil.rmtree('cars_train')
     shutil.rmtree('cars_test')
-    shutil.rmtree('devkit')
+    # shutil.rmtree('devkit')

resnet_152.py

@@ -149,10 +149,10 @@ def resnet152_model(img_rows, img_cols, color_type=1, num_classes=None):
 
     if K.image_dim_ordering() == 'th':
       # Use pre-trained weights for Theano backend
-      weights_path = 'imagenet_models/resnet152_weights_th.h5'
+      weights_path = 'models/resnet152_weights_th.h5'
     else:
       # Use pre-trained weights for Tensorflow backend
-      weights_path = 'imagenet_models/resnet152_weights_tf.h5'
+      weights_path = 'models/resnet152_weights_tf.h5'
 
     model.load_weights(weights_path, by_name=True)
 

resnet_50.py

@@ -142,10 +142,10 @@ def resnet50_model(img_rows, img_cols, color_type=1, num_classes=None):
     # Load ImageNet pre-trained data 
     if K.image_dim_ordering() == 'th':
         # Use pre-trained weights for Theano backend
-        weights_path = 'imagenet_models/resnet50_weights_th_dim_ordering_th_kernels.h5'
+        weights_path = 'models/resnet50_weights_th_dim_ordering_th_kernels.h5'
     else:
         # Use pre-trained weights for Tensorflow backend
-        weights_path = 'imagenet_models/resnet50_weights_tf_dim_ordering_tf_kernels.h5'
+        weights_path = 'models/resnet50_weights_tf_dim_ordering_tf_kernels.h5'
 
     model.load_weights(weights_path)