Self Driving Car Engines

<p align="center"> <a href="#readme"> <img alt="logo" width="50%" src="self-driving.jpeg"> </a> </p> <p align="center"> <a href="#18-lane-augmentation-offroad"><img alt="MIT License" src="https://img.shields.io/badge/License-MIT-yellow.svg"></a> </p>

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Self-Driving-Cars-Engine, Gathers signal processing, computer vision, machine learning and deep learning for self-driving car engines.

What-Done

1. Signal processing (1D smoothing, 2D smoothing, convolution 2 signals, pass-filters)
2. Simple straight lane detection
3. Steering suggestion
4. Multi-lane detection
5. Multi-lane angle
6. Curve-lane detection
7. Car detection using sliding + HOG + eXtreme Boosting
8. Object detection using Tensorflow
9. Distance + Angle for object detection
10. Distance + Speed for object detection
11. Traffic light detection
12. Gradient Smoothing
13. Lane Smoothing
14. Dynamic count lane detection
15. Road Segmentation
16. Plate detection
17. Image Augmentation
18. Lane Augmentation offroad
19. Sensor fusion
20. Kitti-PCL

Results

1. Signal processing

<img src="1.signal-processing/smoothing.png" width="70%" align="">

2. simple straight lane detection

<img src="2.simple-straight-lane/simple-straight-lane-detection.png" width="70%" align="">

3. Steering suggestion

<img src="3.steering-suggestion/steering-suggestion.png" width="70%" align="">

4. Multi-lane detection

<img src="4.multi-lane-detection/multi-lane-detection.png" width="70%" align="">

5. Multi-lane angle

<img src="5.multi-lane-angle/multi-lane-angle.png" width="70%" align="">

6. Curve-lane detection

<img src="6.curve-lane-detection/curve-lane-detection.png" width="70%" align="">

7. Car detection using sliding + HOG + eXtreme Boosting

<img src="7.car-detection-sliding-HOG-XGB/hog-xgb.png" width="70%" align="">

8. Object detection using Tensorflow

<img src="8.object-detection-tensorflow/object-detection-tensorflow.png" width="70%" align="">

9. Distance + Angle for object detection

<img src="9.object-distance-angle/object-distance-angle.png" width="70%" align="">

10. Distance + Speed for object detection

<img src="10.object-distance-speed/object-distance-speed.gif" width="70%" align="">

11. Traffic light detection

<img src="11.traffic-light-detection/traffic-light-detection.png" width="70%" align="">

12. Gradient Smoothing

<img src="12.gradient-smoothing/gradient-smoothing.gif" width="70%" align="">

13. Lane Smoothing

<img src="13.lane-smoothing/lane-smoothing.png" width="70%" align="">

14. Dynamic count lane detection

<img src="14.dynamic-count-lane/dynamic-count-lane.png" width="70%" align="">

15. Road Segmentation

VGG16 Road Segmentation

<img src="15.segmentation/vgg16.png" width="70%" align="">

Mobilenet City Segmentation

<img src="15.segmentation/mobilenet.png" width="70%" align="">

16. Plate detection

<img src="16.plate-detection/plate-detection.jpg" width="70%" align="">

17. Image augmentation

Originally from https://github.com/UjjwalSaxena/Automold--Road-Augmentation-Library

<img src="17.augmentation/augmentation.png" width="70%" align="">

18. Lane Augmentation offroad

<img src="18.lane-augmentation-offroad/lane-augmentation.png" width="70%" align="">

19. Sensor fusion

<img src="19.sensor-fusion/output.gif" width="70%" align="">

20. Pykitti PCL

<img src="20.kitti-pcl/pykitti.png" width="70%" align="">