Update README.md

README.md

@@ -27,12 +27,12 @@ This project builds a self-driving RC car using Raspberry Pi, Arduino and open s
                `data_test.npz`: sample data  
                `train_predict_test.ipynb`: a jupyter notebook that goes through neural network model in OpenCV3  
 
-**raspberrt_pi/**    
+**raspberryPi/**    
        `stream_client.py`:        stream video frames in jpeg format to the host computer  
        `ultrasonic_client.py`:    send distance data measured by sensor to the host computer  
 
 **arduino/**  
-       `rc_keyboard_control.ino`: control rc car controller  
+       `rc_keyboard_control.ino`: control RC car controller  
 
 **computer/**    
        **cascade_xml/**  
@@ -45,14 +45,14 @@ This project builds a self-driving RC car using Raspberry Pi, Arduino and open s
        `model.py`:                 neural network model  
        `model_training.py`:        model training and validation  
        `rc_driver_helper.py`:      helper classes/functions for `rc_driver.py`  
-       `rc_driver.py`:             receive data from raspberry piand drive the rc car based on model prediction
+       `rc_driver.py`:             receive data from raspberry pi and drive the RC car based on model prediction
 
 **Traffic_signal**  
        trafic signal sketch contributed by [@geek111](https://github.com/geek1111)
 
 
 ### How to drive
-1. **Testing:** Flash `rc_keyboard_control.ino` to Arduino and run `rc_control_test.py` to drive the rc car with keyboard. Run `stream_server_test.py` on computer and then run `stream_client.py` on raspberry pi to test video streaming. Similarly, `ultrasonic_server_test.py` and `ultrasonic_client.py` can be used for sensor streaming testing.   
+1. **Testing:** Flash `rc_keyboard_control.ino` to Arduino and run `rc_control_test.py` to drive the RC car with keyboard. Run `stream_server_test.py` on computer and then run `stream_client.py` on raspberry pi to test video streaming. Similarly, `ultrasonic_server_test.py` and `ultrasonic_client.py` can be used for sensor data streaming testing.   
 
 2. **Pi Camera calibration (optional):** Take multiple chess board images using pi camera module at various angles and put them into **`chess_board`** folder, run `picam_calibration.py` and returned parameters from the camera matrix will be used in `rc_driver.py`.