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new c198572 Fix data tutorial (#7329)
c198572 is described below
commit c1985725c4a877a3658cafd4e791aafb4c063e55
Author: Yao Wang <kevinthesu...@gmail.com>
AuthorDate: Mon Aug 7 10:08:11 2017 -0700
Fix data tutorial (#7329)
---
docs/tutorials/basic/data.md | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/docs/tutorials/basic/data.md b/docs/tutorials/basic/data.md
index dba1391..93a1db0 100644
--- a/docs/tutorials/basic/data.md
+++ b/docs/tutorials/basic/data.md
@@ -19,7 +19,7 @@ $ pip install opencv-python requests matplotlib jupyter
```
$ git clone https://github.com/dmlc/mxnet ~/mxnet
-$ MXNET_HOME = '~/mxnet'
+$ export MXNET_HOME='~/mxnet'
```
## MXNet Data Iterator
@@ -366,7 +366,7 @@ Now let's convert them into record io format using the
`im2rec.py` utility scrip
First, we need to make a list that contains all the image files and their
categories:
```python
-os.system('python %s/tools/im2rec.py --list=1 --recursive=1 --shuffle=1
--test-ratio=0.2 data/caltech data/101_ObjectCategories'%MXNET_HOME)
+os.system('python %s/tools/im2rec.py --list=1 --recursive=1 --shuffle=1
--test-ratio=0.2 data/caltech
data/101_ObjectCategories'%os.environ['MXNET_HOME'])
```
The resulting list file (./data/caltech_train.lst) is in the format
`index\t(one or more label)\tpath`. In this case, there is only one label for
each image but you can modify the list to add in more for multi-label training.
@@ -375,7 +375,7 @@ Then we can use this list to create our record io file:
```python
-os.system("python %s/tools/im2rec.py --num-thread=4 --pass-through=1
data/caltech data/101_ObjectCategories"%MXNET_HOME)
+os.system("python %s/tools/im2rec.py --num-thread=4 --pass-through=1
data/caltech data/101_ObjectCategories"%os.environ['MXNET_HOME'])
```
The record io files are now saved at here (./data)
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