correct dockerfile & upgrade to nvidia-docker2

.gitignore

@@ -1,4 +1,5 @@
 data/
 *pyc
 automation/scp_config.yaml
-src/ply
+src/ply
+docker/director-build/*

.python-version

@@ -0,0 +1 @@
+2.7.12

README.rst

@@ -26,6 +26,23 @@ This is the quick version.  If you'd prefer to go step-by-step manually, see Pip
 
 .. _Pipeline_Instructions: https://github.com/RobotLocomotion/LabelFusion/blob/master/docs/pipeline.rst
 
+Camera intrinsic calibration
+---------------------------
+
+For ElasticFusion calibration, create camera.cfg file into your lcm-log folder. camera.cfg is :code:`fx fy px py` in one line.
+
+For render training image, edit :code:`LabelFusion/modules/labelfusion/rendertrainingimages.py` "setCameraInstrinsicsAsus" fuction.
+
+.. code-block:: python
+
+	def setCameraInstrinsicsAsus(view):
+      		principalX = 320.0
+      		principalY = 240.0
+      		focalLength = 617.0 # fx = fy = focalLength
+      		setCameraIntrinsics(view, principalX, principalY, focalLength)
+
+
+
 Collect raw data from Xtion
 ---------------------------
 
@@ -44,6 +61,64 @@ In another, run:
 Your data will be saved in current directory as :code:`lcmlog-*`.
 
 
+Collect raw data from Realsense
+---------------------------
+
+First, install `librealsense  <https://github.com/IntelRealSense/librealsense>`_
+, `intel_ros_relasense <https://github.com/intel-ros/realsense>`_
+and `rgbd_ros_to_lcm <https://github.com/MobileManipulation/rgbd_ros_to_lcm>`_
+
+Second, :code:`cdlf && cd data/logs`, then make a new directory for your data.  In one terminal, run:
+
+::
+
+	roscore
+
+In one, run:
+
+::
+
+	roslaunch realsense2_camera rs_rgbd.launch
+
+modify rgbd_ros_to_lcm topic:
+modify this file ~/catkin_ws/src/rgbd_ros_to_lcm/launch/lcm_republisher.launch to
+
+.. code-block:: 
+
+	<?xml version="1.0"?>
+	<launch>
+	  <node name="lcm_republisher" pkg="rgbd_ros_to_lcm" type="lcm_republisher" output="screen" respawn="false" >
+	    <rosparam subst_value="true">      
+	      # input parameters
+	      subscribe_point_cloud: false
+	      rgb_topic: /camera/color/image_raw
+	      depth_topic: /camera/aligned_depth_to_color/image_raw
+	      cloud_topic: /camera/depth_registered/points
+
+	      # output parameters
+	      output_lcm_channel: "OPENNI_FRAME"
+	      compress_rgb: true
+	      compress_depth: true
+
+	      debug_print_statements: true
+	    </rosparam>
+	  </node>
+	</launch>
+
+and run
+
+::
+
+    roslaunch rgbd_ros_to_lcm lcm_republisher.launch
+
+In another, run:
+
+::
+
+	lcm-logger
+
+Your data will be saved in current directory as :code:`lcmlog-*`.
+
 Process into labeled training data
 ----------------------------------
 

docker/config.sh

@@ -0,0 +1,7 @@
+#!/bin/bash
+#
+# This script define the name of the labelfusion docker image.
+#
+
+#image_name=robotlocomotion/labelfusion:latest
+image_name=ianre657/labelfusion:16.04-latetest

docker/docker_build.sh

@@ -4,9 +4,11 @@
 #
 
 set -exu
+source ./config.sh
 
 root_dir=$(cd $(dirname $0)/../ && pwd)
 
-tag_name=robotlocomotion/labelfusion:test
-
-docker build -f $root_dir/docker/labelfusion.dockerfile -t ${tag_name} $root_dir/docker
+docker build \
+    -f $root_dir/docker/labelfusion.dockerfile \
+    -t ${image_name} \
+    $root_dir/docker

docker/docker_run.sh

@@ -2,17 +2,15 @@
 #
 # Usage:  ./docker_run.sh [/path/to/data]
 #
-# This script calls `nvidia-docker run` to start the labelfusion
-# container with an interactive bash session.  This script sets
-# the required environment variables and mounts the labelfusion
-# source directory as a volume in the docker container.  If the
-# path to a data directory is given then the data directory is
-# also mounted as a volume.
+# This script calls `docker` with `nvidia-docker2 runtime` to start the 
+# labelfusion container with an interactive bash session.  This script 
+# sets the required environment variables and mounts the labelfusion 
+# source directory as a volume in the docker container.  If the path 
+# to a data directory is given then the data directory is also mounted 
+# as a volume.
 #
 
-image_name=robotlocomotion/labelfusion:latest
-
-
+source ./config.sh
 source_dir=$(cd $(dirname $0)/.. && pwd)
 
 if [ ! -z "$1" ]; then
@@ -26,6 +24,15 @@ if [ ! -z "$1" ]; then
   data_mount_arg="-v $data_dir:/root/labelfusion/data"
 fi
 
-xhost +local:root;
-nvidia-docker run -it -e DISPLAY -e QT_X11_NO_MITSHM=1 -v /tmp/.X11-unix:/tmp/.X11-unix:rw -v $source_dir:/root/labelfusion $data_mount_arg --privileged -v /dev/bus/usb:/dev/bus/usb $image_name
-xhost -local:root;
+xhost +
+docker run -it \
+  --rm \
+  --runtime=nvidia \
+  -e DISPLAY \
+  --privileged \
+  -e QT_X11_NO_MITSHM=1 \
+  -v /tmp/.X11-unix:/tmp/.X11-unix:rw \
+  -v $source_dir:/root/labelfusion $data_mount_arg \
+  -v /dev/bus/usb:/dev/bus/usb \
+  $image_name
+xhost -