Eye-Car

Eye-car is a self-driving car project that recognizes the center of the lane without direct maneuvering while driving and recognizes and adjusts the speed when a human handwriting speed signal is read.

Documents

Eye-Car Final Report (한국어)

Demo

Lane Detection

Number Recognition

Members

Team 8

• KAIST 17 Seungho Baek
• KAIST 18 Juyeon Kim
• KAIST 19 ABHIJEET SHARMA

Thx to prof. Sungho Jo, TA. Jungwook Mun, Daekyum Kim

Directory

MazeRunner
└─ src                          (All needed files, Codes, Tests, imgs, models)
    ├─ Study                    (Basic functions we needed)
    ├─ epic_num_reader*.model   (CNN model for number prediction)
    ├─ img                      (Test image sets)
    ├─ tests                    (Files for testing)
    ├─ video                    (Test video sets)
    └─ EyeCar.py                (Main program)

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Getting Started

• src/EyeCar.py, src/epic_num_reader.model required to get started

Clone

• Clone this repo to your local machine using https://github.com/TheStarkor/MazeRunner.git

Prerequisites

Hardware

MODI
Raspberry Pi

Software

Rasbian Buster (2019-09-26 Released)
pyMODI
OpenCV
Tensorflow ver.1
All modules required for tensorflow

Testing

For checking the module connection, we provide test files in the src/tests directory

1. PiCamera/camera_test.py, PiCamera/cap.py for checking Raspberry Pi Camera.

2. ModiTest.py for checking Modi connection and modules working

3. LaneTest.py for lane detection function

4. NumberTest.py for number detction and number prediction

5. (Additional) firebaseTest.py for firebase and firestore connection

Running

$ python EyeCar.py
$ python3 EyeCar.py (If there is python2)