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+### Preparation
+1. Download Images and Annotations from [MSCOCO](http://mscoco.org/dataset/#download). By default, we assume the data is stored in `$HOME/data/coco`
+
+2. Get the coco code. We will call the directory that you cloned coco into `$COCO_ROOT`
+ ```Shell
+ git clone https://github.com/weiliu89/coco.git
+ cd coco
+ git checkout dev
+ ```
+
+3. Build the coco code.
+ ```Shell
+ cd PythonAPI
+ python setup.py build_ext --inplace
+ ```
+
+4. Split the annotation to many files per image and get the image size info.
+ ```Shell
+ # Check scripts/batch_split_annotation.py and change settings accordingly.
+ python scripts/batch_split_annotation.py
+ # Create the minival2014_name_size.txt and test-dev2015_name_size.txt in $CAFFE_ROOT/data/coco
+ python scripts/batch_get_image_size.py
+ ```
+
+5. Create the LMDB file.
+ ```Shell
+ cd $CAFFE_ROOT
+ # Create the minival.txt, testdev.txt, test.txt, train.txt in data/coco/
+ python data/coco/create_list.py
+ # You can modify the parameters in create_data.sh if needed.
+ # It will create lmdb files for minival, testdev, test, and train with encoded original image:
+ # - $HOME/data/coco/lmdb/coco_minival_lmdb
+ # - $HOME/data/coco/lmdb/coco_testdev_lmdb
+ # - $HOME/data/coco/lmdb/coco_test_lmdb
+ # - $HOME/data/coco/lmdb/coco_train_lmdb
+ # and make soft links at examples/coco/
+ ./data/coco/create_data.sh
+ ```