[image-classification] default use min_random_scale=1, add data/image…

…net1k-val.sh (apache#4295)

example/image-classification/data/imagenet1k-val.sh

@@ -0,0 +1,22 @@
+#!/bin/bash
+
+# This file download the imagnet-1k validation dataset and convert it into a rec
+# file. One need to provide the URL for the ILSVRC2012_img_val.tar, which can be
+# find at http://www.image-net.org/download-images
+#
+# Example usage (replace the URL with the correct one):
+# ./imagenet1k-val.sh http://xxxxxx/challenges/LSVRC/2012/nnoupb/ILSVRC2012_img_val.tar
+
+if [ ! -e ILSVRC2012_img_val.tar ]; then
+    wget $1
+fi
+mkdir -p val
+tar -xf ILSVRC2012_img_val.tar -C val
+wget http://data.mxnet.io/models/imagenet/resnet/val.lst -O imagenet1k-val.lst
+
+CUR_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
+MX_DIR=${CUR_DIR}/../../../
+
+python ${CUR_DIR}/../../../tools/im2rec.py --resize 256 --quality 90 --num-thread 16 imagenet1k-val val/
+
+rm -rf val

example/image-classification/train_imagenet.py

@@ -23,7 +23,8 @@
         num_classes      = 1000,
         num_examples     = 1281167,
         image_shape      = '3,224,224',
-        min_random_scale = 0.533, # assume input image has min size 480, 0.533 = 256/480
+        min_random_scale = 1, # if input image has min size k, suggest to use
+                              # 256.0/x, e.g. 0.533 for 480
         # train
         num_epochs       = 80,
         lr_step_epochs   = '30,60',