Commit 4fdadcfb authored by Svetlana Pavlitskaya's avatar Svetlana Pavlitskaya

Update README.md

parent d9ce627a
# Development and deployment of a CNN component using EMADL2CPP
1. [ How to develop and train a CNN component using EMADL2CPP](#nn)
2. [ How to build and run the app ](#app)
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# Development and training of a CNN component using EMADL2CPP
## Prerequisites
* Linux. Ubuntu Linux 16.04 and 18.04 were used during testing.
......@@ -72,7 +76,8 @@ configuration VGG16{
4. When the target code is generated, the corresponding trainer file (e.g. `CNNTrainer_<root_model_name>.py` in case of MXNet) can be executed.
# Development and deployment of an application for TORCS
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# Building and running an application for TORCS
## Prerequisites
1. Linux. Ubuntu Linux 16.04 and 18.04 were used during testing.
......@@ -111,3 +116,10 @@ Further installation help can be found in the Readme file provided with the Deep
4. Use `F2` key to switch between camera modes to select the mode when the car or it's parts are not visible
5. Use `PgUp/PgDown` keys to switch between cars and select `chenyi` - the car that does not drive on its own
## Code generation and running the project
1. Download and unpack the [archive]() that contains all EMA and EMADL component for an application
2. Run `generate.sh` script. It will generate the code to the `target` folder, copy the handwritten part of the project (communication with TORCS via shared memory) as well as the weights of the trained CNN and finally build the project
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)
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