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 # **AutonomousCarAI**
 ## Description
 
-Training a car to drive autonomously. A deep learning implementation of simple self driving car.  The aim of the project is to train a car to drive in a game terrain by capturing the frames and the keys. Each frame has been converted to a *1x2700* numpy array corresponds to which there are keys *w,s,a,d*.
+Training a car to drive autonomously. This is a deep learning implementation of a simple self driving car.  The aim of the project is to train a car to drive in a game terrain by capturing the frames and the keys. Each frame has been converted to a *1x2700* NumPy array which corresponds to keys *w,s,a,d*.
 
 ## Prerequisites
 
-The python libraries used to capture frames is ***win32api*** which is only available on windows. So it cant run on linux. As an alteranative ***pyscreenshot*** can be used in linux but its extremly slow to capture frames ~ 10fps. ***Keras*** with tensorflow backend has been used to train the model. 
+The Python libraries used to capture frames is ***win32api*** which is only available on Windows-- it cannot run on Linux. As an alternative ***pyscreenshot*** can be used in Linux but its extremely slow to capture frames ~ 10fps. ***Keras*** with tensorflow backend has been used to train the model.
 
 
 
 ## How it works?
 
- - Run the ***game.exe***, once the red screen with the note "Press Space" appears run ***main.py*** Let main.py know the location of the game. So dont press space unless it finds the game screen.
- - ***main.py*** will capture the location of the game and will ask whether to train, test or quit. 
+ - Run the ***game.exe***, once the red screen appears with the note "Press Space", run ***main.py*** Let main.py know the location of the game. Do not press space unless it finds the game screen.
+ - ***main.py*** will capture the location of the game and will ask whether to train, test or quit.
  - Choose an option:
-**Training** use *w*, *a*, *s*, *d* to move the car on the road and press *q* to stop training. This will collect data and store to data/ folder. Once data has been collected , use run ***model.py*** to create a trained model for the self driving car  in the *model/* folder. Now this model can be used for 
-**Testing** Testing here refers to driving. Once there is a trained model, this option can be used. Just select the option and let the car drive itself. To stop testing, put the cursor on the opencv screen windows and press *esc*.
+**Training** use *w*, *a*, *s*, *d* to move the car on the road and press *q* to stop training. This will collect data and store to data/ folder. Once the data has been collected, use run ***model.py*** to create a trained model for the self driving car  in the *model/* folder. Now this model can be used for
+**Testing** Testing here refers to driving. Once there is a trained model, this option can be used. Just select the option and let the car drive itself. To stop testing, put the cursor on the opencv screen window and press *esc*.
 
 
 
 
 ## Game Link
 
-The link of the car game to be trained 
+The link of the car game to be trained:
 https://www.dropbox.com/s/ul3s4i0trnohsih/game.zip?dl=0
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