https://github.com/robincpc/carnd

Projects for Udacity Self-driving Car NanoDegree :car::dash:
https://github.com/robincpc/carnd

self-driving-car udacity-carnd

Last synced: 8 months ago
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Projects for Udacity Self-driving Car NanoDegree :car::dash:

• Host: GitHub
• URL: https://github.com/robincpc/carnd
• Owner: RobinCPC
• License: mit
• Created: 2017-04-22T00:45:05.000Z (about 9 years ago)
• Default Branch: master
• Last Pushed: 2017-08-24T22:22:49.000Z (over 8 years ago)
• Last Synced: 2025-02-08T15:46:34.515Z (about 1 year ago)
• Topics: self-driving-car, udacity-carnd
• Language: Python
• Homepage:
• Size: 21.7 MB
• Stars: 0
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# CarND

[![Udacity - Self-Driving Car NanoDegree](https://s3.amazonaws.com/udacity-sdc/github/shield-carnd.svg)](http://www.udacity.com/drive)

![License](https://img.shields.io/badge/license-MIT-blue.svg)

### This repository collects all my project results of Udacity Self-Driving Car NanoDegree.

![demo gif](./demo.gif)

The above shows the result of final project (Term 1). Here is the [youtube link](https://youtu.be/pgGpdRIRMuE) of the results.

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## Project 5: Vehicle Detection and Tracking

![visualized output](https://github.com/RobinCPC/CarND-Vehicle-Detection/blob/master/output_images/project_output.jpg)

Created a vehicle detection and tracking pipeline with OpenCV, histogram of oriented gradients (HOG), and support vector machines (SVM). Optimized and evaluated the model on video data from a automotive camera taken during highway driving. For more detail, please click [writeup](https://nbviewer.jupyter.org/github/RobinCPC/CarND-Vehicle-Detection/blob/master/writeup.ipynb).

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## Project 4: Advanced Lane Finding

![visualized output](https://github.com/RobinCPC/CarND-Advanced-Lane-Lines/blob/master/output_images/project_output.jpg)

Built an advanced lane-finding algorithm using distortion correction, image rectification, color transforms, and gradient thresholding. Identified lane curvature and vehicle displacement. Overcame environmental challenges such as shadows and pavement changes. For more detail, please click [writeup](https://nbviewer.jupyter.org/github/RobinCPC/CarND-Advanced-Lane-Lines/blob/master/project_output.ipynb).

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## Project 3: Use Deep Learning to Clone Driving Behavior

![sample images](https://github.com/RobinCPC/CarND-Behavioral-Cloning-P3/blob/master/examples/screenshot.png)

Built and trained a convolutional neural network for end-to-end driving in a simulator, using TensorFlow and Keras. Used optimization techniques such as regularization and dropout to generalize the network for driving on multiple tracks. For more detail, please click [writeup](https://nbviewer.jupyter.org/github/RobinCPC/CarND-Behavioral-Cloning-P3/blob/master/writeup_report.ipynb).

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## Project 2: Traffic Sign Classification

![sample images](https://github.com/RobinCPC/CarND-Traffic-Sign-Classifier-Project/blob/master/examples/ten_sample.png)

![visualized CNN](https://github.com/RobinCPC/CarND-Traffic-Sign-Classifier-Project/blob/master/visualize_cnn.png)

Built and trained a deep neural network to classify traffic signs, using TensorFlow. Experimented with different network architectures. Performed image pre-processing and validation to guard against overfitting. Please click [ipynb](https://github.com/RobinCPC/CarND-Traffic-Sign-Classifier-Project/blob/master/Traffic_Sign_Classifier.ipynb) for more detial.

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## Project 1: Finding Lane Lines on the Road



Detected highway lane lines on a video stream. Used OpencV image analysis techniques to identify lines, including Hough Transforms and Canny edge detection. For more detail, please click [nbviewer](https://nbviewer.jupyter.org/github/RobinCPC/CarND-LaneLines-P1/blob/master/P1.ipynb)