Update README.md: Removed wrong installation for unsupported armadillo version

README.md

@@ -81,10 +81,10 @@ configuration VGG16{
 
 ## Prerequisites
 1. Linux. Ubuntu Linux 16.04 and 18.04 were used during testing.
-2. Armadillo (at least armadillo version 6.600 must be used). [official instructions at Armadillo Website](http://arma.sourceforge.net/download.html).
+2. Armadillo (at least armadillo version 6.600 must be used) [Official instructions at Armadillo Website](http://arma.sourceforge.net/download.html).
 3. ROS, Java runtime environment, GCC/Clang and armadillo - install using your linux distribution tools, e.g. apt in Ubuntu:
 
-    ```apt-get install ros-base-dev clang openjdk-8-jre libarmadillo-dev```
+    ```apt-get install ros-base-dev clang openjdk-8-jre```
 4. MXNet - install using [official instructions at MXNet Website](https://mxnet.incubator.apache.org/) for C++
 5. TORCS (see below)
 
@@ -124,32 +124,44 @@ Further installation help can be found in the Readme file provided with the Deep
 3. Start TORCS and configure race as described above. Select mode where host car is not visible
 4. Go to the `target` folder and start `run.sh` script. It will open two three terminals: one for the ROS core, one for the TORCSCOmponent (application part responsible for communication with TORCS) and one for the Mastercomponent (application part generated from the models at step 2 which is repsondible for application logic)
 
-#Troubleshooting Help
+# Troubleshooting Help
 
-Error: CNNPredictor_dp_mastercomponent_dpnet.h:4:33: fatal error: mxnet/c_predict_api.h: No such file or directory
-Fix:
+ERROR: CNNPredictor_dp_mastercomponent_dpnet.h:4:33: fatal error: mxnet/c_predict_api.h: No such file or directory.
+
+FIX:
 Copy compiled mxnet lib and include files to usr/lib and usr/include respectively. Replace YOUR_MXNET_REPOSITORY with your corresponding information:
-```cd YOUR_MXNET_REPOSITORY/incubator-mxnet/lib
+```
+cd YOUR_MXNET_REPOSITORY/incubator-mxnet/lib
 sudo cp * /usr/lib
 cd YOUR_MXNET_REPOSITORY/incubator-mxnet/include
-sudo cp -r * /usr/include```
+sudo cp -r * /usr/include
+```
 
 
-Error: HelperA.h:79:28: error: ‘sqrtmat’ was not declared in this scope
-Fix:
+ERROR: HelperA.h:79:28: error: ‘sqrtmat’ was not declared in this scope.
+
+FIX:
 Copy compiled armadillo lib and include files to usr/lib and usr/include respectively. Replace YOUR_ARMADILLO_REPOSITORY and VERSION (e.g. 8.500.1) with your corresponding information:
-```cd YOUR_ARMADILLO_REPOSITORY/armadillo-VERSION
+```
+cd YOUR_ARMADILLO_REPOSITORY/armadillo-VERSION
 sudo cp libarmadillo* /usr/lib
 cd YOUR_ARMADILLO_REPOSITORY/armadillo-VERSION/include
-sudo cp -r * /usr/include```
+sudo cp -r * /usr/include
+```
 
-Error: Coordinator_dp_mastercomponent.cpp.o: undefined reference to symbol 'dsyrk_' usr/lib/libopenblas.so.0: error adding symbols: DSO missing from command line (after executing Run generate2ros.sh)
-Fix:
+ERROR: Coordinator_dp_mastercomponent.cpp.o: undefined reference to symbol 'dsyrk_' usr/lib/libopenblas.so.0: error adding symbols: DSO missing from command line (after executing Run generate2ros.sh).
+
+FIX:
 Once generate2ros.sh was executed, modify the file YOUR_TORCSDL_REPOSITORY/torcs_dl/doc/deep_driving_project/target/Mastercomponent/dp_mastercomponent/coordinator/CMakeLists.txt to include the blas and openblas libraries, i.e.:
-```target_link_libraries(Coordinator_dp_mastercomponent RosAdapter_dp_mastercomponent dp_mastercomponent Threads::Threads -lblas -lopenblas)```
+```
+target_link_libraries(Coordinator_dp_mastercomponent RosAdapter_dp_mastercomponent dp_mastercomponent Threads::Threads -lblas -lopenblas)
+```
 
 Then navigate to YOUR_TORCSDL_REPOSITORY/torcs_dl/doc/deep_driving_project/target and execute build_all.sh. Make sure you delete the build folders to remove the existed compilation configurations for both components:
-```cd YOUR_TORCSDL_REPOSITORY/torcs_dl/doc/deep_driving_project/target
-bash build_all.sh```
+```
+cd YOUR_TORCSDL_REPOSITORY/torcs_dl/doc/deep_driving_project/target
+bash build_all.sh
+```
+
 
 Finally, the deep driving project will be compiled successfully.