update

ace19-dev · Aug 8, 2019 · e5db632 · e5db632
1 parent 2285615
commit e5db632
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Showing 3 changed files with 11 additions and 11 deletions.
diff --git a/train.py b/train.py
@@ -41,7 +41,7 @@
 
 flags.DEFINE_enum('learning_policy', 'poly', ['poly', 'step'],
                   'Learning rate policy for training.')
-flags.DEFINE_float('base_learning_rate', 0.003,
+flags.DEFINE_float('base_learning_rate', 0.002,
                    'The base learning rate for model training.')
 flags.DEFINE_float('learning_rate_decay_factor', 1e-4,
                    'The rate to decay the base learning rate.')
@@ -62,7 +62,7 @@
                      'Initialize the last layer.')
 flags.DEFINE_boolean('last_layers_contain_logits_only', False,
                      'Only consider logits as last layers or not.')
-flags.DEFINE_integer('slow_start_step', 686,
+flags.DEFINE_integer('slow_start_step', 0,
                      'Training model with small learning rate for few steps.')
 flags.DEFINE_float('slow_start_learning_rate', 0.0003,
                    'Learning rate employed during slow start.')
@@ -77,8 +77,8 @@
 #                     None,
 #                     'Saved checkpoint path.')
 flags.DEFINE_string('pre_trained_checkpoint',
-                    # 'pre-trained/resnet_v2_50.ckpt',
-                    None,
+                    'pre-trained/resnet_v2_50.ckpt',
+                    # None,
                     'The pre-trained checkpoint in tensorflow format.')
 flags.DEFINE_string('checkpoint_exclude_scopes',
                     'resnet_v2_50/logits,resnet_v2_50/SpatialSqueeze,resnet_v2_50/predictions',

diff --git a/utils/train_utils.py b/utils/train_utils.py
@@ -315,7 +315,7 @@ def restore_fn(flags):
     #
     # Warn the user if a checkpoint exists in the train_dir. Then ignore.
     # if tf.train.latest_checkpoint(flags.train_dir):
-    #     tf.logging.info(
+    #     tf.compat.v1.logging.info(
     #         'Ignoring --checkpoint_path because a checkpoint already exists in %s'
     #         % flags.train_dir)
     #     return None
@@ -344,7 +344,7 @@ def restore_fn(flags):
 
     slim.assign_from_checkpoint_fn(flags.pre_trained_checkpoint,
                                    variables_to_restore)
-    tf.logging.info('Fine-tuning from %s. Ignoring missing vars: %s' %
+    tf.compat.v1.logging.info('Fine-tuning from %s. Ignoring missing vars: %s' %
                     (flags.pre_trained_checkpoint, flags.ignore_missing_vars))
 
 

diff --git a/val_data.py b/val_data.py
@@ -70,14 +70,14 @@ def augment(self, filename, image, label):
         """
         # image = tf.image.central_crop(image, 0.9)
         # image = tf.image.random_flip_up_down(image)
-        # image = tf.image.random_flip_left_right(image)
-        # image = tf.image.rot90(image, k=random.randint(0,4))
+        image = tf.image.random_flip_left_right(image)
+        image = tf.image.rot90(image, k=random.randint(0,4))
         # paddings = tf.constant([[11, 11], [11, 11], [0, 0]])  # 224
         # image = tf.pad(image, paddings, "CONSTANT")
-        image = tf.image.random_brightness(image, max_delta=1.1)
-        image = tf.image.random_contrast(image, lower=0.9, upper=1.1)
+        image = tf.image.random_brightness(image, max_delta=1.2)
+        image = tf.image.random_contrast(image, lower=0.8, upper=1.2)
         # image = tf.image.random_hue(image, max_delta=0.04)
-        image = tf.image.random_saturation(image, lower=0.9, upper=1.1)
+        image = tf.image.random_saturation(image, lower=0.8, upper=1.2)
         # image = tf.image.resize(image, [self.resize_h, self.resize_w])
 
         return filename, image, label