From 9f55241644b8a0f251ec8455599c59e049bfd62c Mon Sep 17 00:00:00 2001
From: JuneChul Roh
Date: Tue, 15 Dec 2020 13:35:00 -0600
Subject: Minor update to README.md
---
README.md | 6 +++---
docker/README.md | 46 +++++++++++++++++++++++-----------------------
docker/README.pdf | Bin 148734 -> 0 bytes
3 files changed, 26 insertions(+), 26 deletions(-)
delete mode 100644 docker/README.pdf
diff --git a/README.md b/README.md
index 87b2b33..75b6817 100644
--- a/README.md
+++ b/README.md
@@ -32,11 +32,11 @@ The TI Vision Apps Library is a set of APIs for the target deployment that are d
The TI Vision Apps Library is included in the pre-built package of [J721E Processor SDK RTOS 7.1.0](https://software-dl.ti.com/jacinto7/esd/processor-sdk-rtos-jacinto7/latest/index_FDS.html).
## How to Set Up TI OpenVX + ROS Docker Container Environment on J7 Target
-Click to download docker/README.pdf
+Click to Download J7ROS_Docker_README.pdf
-Click to download docker/README.pdf
+
-For debugging (Caution: there are formatting issues): [docker/README.md](docker/README.md)
+For debugging (Caution: there is formatting issue): [docker/README.md](docker/README.md)
## TI OpenVX + ROS Demo Applications
diff --git a/docker/README.md b/docker/README.md
index 5bfe8cc..b1c3c04 100644
--- a/docker/README.md
+++ b/docker/README.md
@@ -16,7 +16,7 @@ This TI OpenVX + ROS development framework works with [pre-built package](https:
### Ubuntu PC
A Ubuntu (18.04 recommended) PC is required. For RViz visualization of input/output topics published from the J7, it is assumed that ROS (Melodic recommended) is installed on the Ubuntu PC.
-Once finding the IP address assigned to J7 EVM (using a serial port communications program, for example, `minicom`), connect to J7 Linux with SSH:
+Once finding the IP address assigned to J7 EVM (using a serial port communications program, for example, `minicom`), connect to J7 Linux with SSH:
```
ssh root@
```
@@ -41,7 +41,7 @@ Figure 1 shows the hardware setup and high-level installation steps on the J7 ta
## Clone Git Repository
-1. Set up the project directory and the catkin workspace:
+1. Set up the project directory and the catkin workspace:
```
WORK_DIR=$HOME/j7ros_home
CATKIN_WS=$WORK_DIR/catkin_ws
@@ -50,20 +50,20 @@ Figure 1 shows the hardware setup and high-level installation steps on the J7 ta
cd $CATKIN_WS/src
```
-2. Clone the project GIT repository:
+2. Clone the project GIT repository:
```
git clone https://git.ti.com/git/processor-sdk-vision/jacinto_ros_perception.git
```
## Download TIDL Model & ROSBAG File
-1. For convenience, set up following soft-links:
+1. For convenience, set up following soft-links:
```
cd $WORK_DIR
ln -s $CATKIN_WS/src/jacinto_ros_perception/docker/Makefile
```
-2. To download data files, run the following in `$WORK_DIR`:
+2. To download data files, run the following in `$WORK_DIR`:
```
make data_download
```
@@ -75,13 +75,13 @@ Figure 1 shows the hardware setup and high-level installation steps on the J7 ta
1. Following [this link](https://docs.docker.com/get-started/#test-docker-installation),
check that Docker and network work correctly on the J7 host Linux.
-2. To generate bash scripts for building and running a Docker image for the project:
+2. To generate bash scripts for building and running a Docker image for the project:
```
make scripts
```
Make sure that two bash scripts named `docker_build.sh` and `docker_run.sh` are generated.
-3. To build the Docker image, at `$WORK_DIR` run:
+3. To build the Docker image, at `$WORK_DIR` run:
```
./docker_build.sh
```
@@ -93,7 +93,7 @@ check that Docker and network work correctly on the J7 host Linux.
## Set Up Remote PC for Visualization
Open another terminal on Ubuntu PC to set up environment for RViz visualization.
-1. Clone GIT repository:
+1. Clone GIT repository:
```
CATKIN_WS=$HOME/j7ros_home/catkin_ws
mkdir -p $CATKIN_WS/src
@@ -101,25 +101,25 @@ Open another terminal on Ubuntu PC to set up environment for RViz visualization.
git clone https://git.ti.com/git/processor-sdk-vision/jacinto_ros_perception.git
```
-2. Build ROS nodes:
+2. Build ROS nodes:
```
cd $CATKIN_WS
catkin_make
```
-3. ROS network setting: For convenience, set up a soft-link:
+3. ROS network setting: For convenience, set up a soft-link:
```
ln -s src/jacinto_ros_perception/setup_env_pc.sh
```
- Update the following lines in `setup_env_pc.sh`:
+ Update the following lines in `setup_env_pc.sh`:
```
PC_IP_ADDR=
J7_IP_ADDR=
```
`` can be found by running `make ip_show` on **J7 terminal**.
- To set up the PC environment, run the following:
+ To set up the PC environment, run the following:
```
source setup_env_pc.sh
```
@@ -129,12 +129,12 @@ After launching ROS nodes on the J7, we can check the all the ROS topics by runn
## Build Demo ROS Applications
-1. To run the docker image:
+1. To run the docker image:
```
./docker_run.sh
```
-2. To build ROS applications, inside the Docker container:
+2. To build ROS applications, inside the Docker container:
```
cd $CATKIN_WS
catkin_make
@@ -143,47 +143,47 @@ After launching ROS nodes on the J7, we can check the all the ROS topics by runn
## Run Stereo Vision Application
-1. **[J7]** To launch `ti_sde` node with playing back a ROSBAG file, run the following in `$WORK_DIR` on the J7 host Linux:
+1. **[J7]** To launch `ti_sde` node with playing back a ROSBAG file, run the following in `$WORK_DIR` on the J7 host Linux:
```
./docker_run.sh roslaunch ti_sde bag_sde.launch
```
- Alternatively, you can run the following `roslaunch` command **inside** the Docker container:
+ Alternatively, you can run the following `roslaunch` command **inside** the Docker container:
```
roslaunch ti_sde bag_sde.launch
```
-2. **[Remote PC]** For visualization, on the PC:
+2. **[Remote PC]** For visualization, on the PC:
```
roslaunch ti_sde rviz.launch
```
## Run CNN Semantic Segmentation Application
-1. **[J7]** To launch `ti_semseg_cnn` node with playing back a ROSBAG file, run the following in `$WORK_DIR` on the J7 host Linux:
+1. **[J7]** To launch `ti_semseg_cnn` node with playing back a ROSBAG file, run the following in `$WORK_DIR` on the J7 host Linux:
```
./docker_run.sh roslaunch ti_semseg_cnn bag_semseg_cnn.launch
```
- Alternatively, you can run the following `roslaunch` command **inside** the Docker container:
+ Alternatively, you can run the following `roslaunch` command **inside** the Docker container:
```
roslaunch ti_semseg_cnn bag_semseg_cnn.launch
```
-2. **[Remote PC]** For visualization, on the PC:
+2. **[Remote PC]** For visualization, on the PC:
```
roslaunch ti_semseg_cnn rviz.launch
```
## Run Stereo Vision and CNN Semantic Segmentation Together
-1. **[J7]** To launch `ti_sde` and `ti_semseg_cnn` together with playing back a ROSBAG file, run the following in `$WORK_DIR` on the J7 host Linux:
+1. **[J7]** To launch `ti_sde` and `ti_semseg_cnn` together with playing back a ROSBAG file, run the following in `$WORK_DIR` on the J7 host Linux:
```
./docker_run.sh roslaunch ti_sde bag_sde_semseg.launch
```
- Alternatively, you can run the following `roslaunch` command **inside** the Docker container:
+ Alternatively, you can run the following `roslaunch` command **inside** the Docker container:
```
roslaunch ti_sde bag_sde_semseg.launch
```
-2. **[Remote PC]** For visualization, on the PC:
+2. **[Remote PC]** For visualization, on the PC:
```
roslaunch ti_sde rviz_sde_semseg.launch
```
diff --git a/docker/README.pdf b/docker/README.pdf
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