From acce1cf983b9dd6d49163d0716b786e46dd3327e Mon Sep 17 00:00:00 2001
From: Joshua Zhang <cheungchih@gmail.com>
Date: Wed, 16 Nov 2016 17:48:54 -0600
Subject: [PATCH] minor fixes for training, fix float/double initializer in
 mxnet

---
 config/config.py    | 11 ++++++-----
 dataset/iterator.py |  2 +-
 mxnet               |  2 +-
 3 files changed, 8 insertions(+), 7 deletions(-)

diff --git a/config/config.py b/config/config.py
index ceff576..d2bdbcf 100644
--- a/config/config.py
+++ b/config/config.py
@@ -12,8 +12,9 @@
     RandCropper(min_scale=.3, min_aspect_ratio=.5, max_aspect_ratio=2., min_overlap=.3),
     RandCropper(min_scale=.3, min_aspect_ratio=.5, max_aspect_ratio=2., min_overlap=.5),
     RandCropper(min_scale=.3, min_aspect_ratio=.5, max_aspect_ratio=2., min_overlap=.7),
-    RandCropper(min_scale=.3, min_aspect_ratio=.5, max_aspect_ratio=2., min_overlap=.9),
-    RandCropper(min_scale=.3, min_aspect_ratio=.5, max_aspect_ratio=2., min_overlap=1.0)]
+    RandPadder(max_scale=2., min_aspect_ratio=.5, max_aspect_ratio=2., min_gt_scale=.05),
+    RandPadder(max_scale=3., min_aspect_ratio=.5, max_aspect_ratio=2., min_gt_scale=.05),
+    RandPadder(max_scale=4., min_aspect_ratio=.5, max_aspect_ratio=2., min_gt_scale=.05),]
 # cfg.TRAIN.RAND_SAMPLERS = []
 cfg.TRAIN.RAND_MIRROR = True
 cfg.TRAIN.INIT_SHUFFLE = True
@@ -25,7 +26,7 @@
 # validation
 cfg.VALID = edict()
 cfg.VALID.RAND_SAMPLERS = []
-cfg.VALID.RAND_MIRROR = True
-cfg.VALID.INIT_SHUFFLE = True
-cfg.VALID.EPOCH_SHUFFLE = True
+cfg.VALID.RAND_MIRROR = False
+cfg.VALID.INIT_SHUFFLE = False
+cfg.VALID.EPOCH_SHUFFLE = False
 cfg.VALID.RAND_SEED = None
diff --git a/dataset/iterator.py b/dataset/iterator.py
index b3243b2..b1a04e9 100644
--- a/dataset/iterator.py
+++ b/dataset/iterator.py
@@ -167,7 +167,7 @@ def _data_augmentation(self, data, label):
                     offset_x = 0 - xmin
                     offset_y = 0 - ymin
                     data_bak = data
-                    data = np.full((new_height, new_width, 3), 255)
+                    data = np.full((new_height, new_width, 3), 128.)
                     data[offset_y:offset_y+height, offset_x:offset_x + width, :] = data_bak
                 label = rand_crops[index][1]
 
diff --git a/mxnet b/mxnet
index ae6b072..ecdead0 160000
--- a/mxnet
+++ b/mxnet
@@ -1 +1 @@
-Subproject commit ae6b072ca18f24631fb9e81d65f3f36c90c68fa7
+Subproject commit ecdead06fcc9c8c7cb397f9ec7a76496316940a0