Use curl to download sample data instead of wget. (#13761)

scala-package/examples/scripts/infer/imageclassifier/get_resnet_18_data.sh

@@ -34,8 +34,8 @@ if [ ! -d "$image_path" ]; then
 fi
 
 if [ ! -f "$data_path" ]; then
-  wget https://s3.us-east-2.amazonaws.com/scala-infer-models/resnet-18/resnet-18-symbol.json -P $data_path
-  wget https://s3.us-east-2.amazonaws.com/scala-infer-models/resnet-18/resnet-18-0000.params -P $data_path
-  wget https://s3.us-east-2.amazonaws.com/scala-infer-models/resnet-18/synset.txt -P $data_path
-  wget https://s3.us-east-2.amazonaws.com/mxnet-scala/scala-example-ci/resnet152/kitten.jpg -P $image_path
+  curl https://s3.us-east-2.amazonaws.com/scala-infer-models/resnet-18/resnet-18-symbol.json -o $data_path/resnet-18-symbol.json
+  curl https://s3.us-east-2.amazonaws.com/scala-infer-models/resnet-18/resnet-18-0000.params -o $data_path/resnet-18-0000.params
+  curl https://s3.us-east-2.amazonaws.com/scala-infer-models/resnet-18/synset.txt -o $data_path/synset.txt
+  curl https://s3.us-east-2.amazonaws.com/mxnet-scala/scala-example-ci/resnet152/kitten.jpg -o $image_path/kitten.jpg
 fi

scala-package/examples/scripts/infer/imageclassifier/get_resnet_data.sh

@@ -34,8 +34,8 @@ if [ ! -d "$image_path" ]; then
 fi
 
 if [ ! -f "$data_path" ]; then
-  wget https://s3.us-east-2.amazonaws.com/mxnet-scala/scala-example-ci/resnet152/resnet-152-0000.params -P $data_path
-  wget https://s3.us-east-2.amazonaws.com/mxnet-scala/scala-example-ci/resnet152/resnet-152-symbol.json -P $data_path
-  wget https://s3.us-east-2.amazonaws.com/mxnet-scala/scala-example-ci/resnet152/synset.txt -P $data_path
-  wget https://s3.us-east-2.amazonaws.com/mxnet-scala/scala-example-ci/resnet152/kitten.jpg -P $image_path
+  curl https://s3.us-east-2.amazonaws.com/mxnet-scala/scala-example-ci/resnet152/resnet-152-0000.params -o $data_path/resnet-152-0000.params
+  curl https://s3.us-east-2.amazonaws.com/mxnet-scala/scala-example-ci/resnet152/resnet-152-symbol.json -o $data_path/resnet-152-symbol.json
+  curl https://s3.us-east-2.amazonaws.com/mxnet-scala/scala-example-ci/resnet152/synset.txt -o $data_path/synset.txt
+  curl https://s3.us-east-2.amazonaws.com/mxnet-scala/scala-example-ci/resnet152/kitten.jpg -o $image_path/kitten.jpg
 fi

scala-package/examples/scripts/infer/objectdetector/get_ssd_data.sh

@@ -35,12 +35,11 @@ if [ ! -d "$image_path" ]; then
 fi
 
 if [ ! -f "$data_path" ]; then
-    wget https://s3.amazonaws.com/model-server/models/resnet50_ssd/resnet50_ssd_model-symbol.json -P $data_path
-    wget https://s3.amazonaws.com/model-server/models/resnet50_ssd/resnet50_ssd_model-0000.params -P $data_path
-    wget https://s3.amazonaws.com/model-server/models/resnet50_ssd/synset.txt -P $data_path
-    cd $image_path
-    wget https://cloud.githubusercontent.com/assets/3307514/20012566/cbb53c76-a27d-11e6-9aaa-91939c9a1cd5.jpg -O 000001.jpg
-    wget https://cloud.githubusercontent.com/assets/3307514/20012567/cbb60336-a27d-11e6-93ff-cbc3f09f5c9e.jpg -O dog.jpg
-    wget https://cloud.githubusercontent.com/assets/3307514/20012563/cbb41382-a27d-11e6-92a9-18dab4fd1ad3.jpg -O person.jpg
+    curl https://s3.amazonaws.com/model-server/models/resnet50_ssd/resnet50_ssd_model-symbol.json -o $data_path/resnet50_ssd_model-symbol.json
+    curl https://s3.amazonaws.com/model-server/models/resnet50_ssd/resnet50_ssd_model-0000.params -o $data_path/resnet50_ssd_model-0000.params
+    curl https://s3.amazonaws.com/model-server/models/resnet50_ssd/synset.txt -o $data_path/synset.txt
+    curl https://cloud.githubusercontent.com/assets/3307514/20012566/cbb53c76-a27d-11e6-9aaa-91939c9a1cd5.jpg -o $image_path/000001.jpg
+    curl https://cloud.githubusercontent.com/assets/3307514/20012567/cbb60336-a27d-11e6-93ff-cbc3f09f5c9e.jpg -o $image_path/dog.jpg
+    curl https://cloud.githubusercontent.com/assets/3307514/20012563/cbb41382-a27d-11e6-92a9-18dab4fd1ad3.jpg -o $image_path/person.jpg
 fi
 

scala-package/examples/scripts/rnn/run_test_charrnn.sh

@@ -27,7 +27,7 @@ else
 fi
 
 # you can get the training data file using the following command
-# wget http://data.mxnet.io/data/char_lstm.zip
+# curl -O http://data.mxnet.io/data/char_lstm.zip
 # unzip -o char_lstm.zip
 # for example ./datas/obama.txt
 DATA_PATH=$1

scala-package/examples/scripts/rnn/run_train_charrnn.sh

@@ -28,7 +28,7 @@ fi
 # which gpu card to use, -1 means cpu
 GPU=$1
 # you can get the training data file using the following command
-# wget http://data.mxnet.io/data/char_lstm.zip
+# curl -O http://data.mxnet.io/data/char_lstm.zip
 # unzip -o char_lstm.zip
 # for example ./datas/obama.txt
 DATA_PATH=$2