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Automold--Road-Augmentation-Library
This library augments road images to introduce various real world scenarios that pose challenges for training neural networks of Autonomous vehicles. Automold is created to train CNNs in specific weather and road conditions.CarND-Advanced-Lane-Lines-Detection-T1P4
This is the advanced lane detection project which includes advanced image processing to detect lanes irrespective of the road texture, brightness, contrast etc. I used Image warping and sliding window approach to find and plot the lanes. This makes it better with the lane curves.Semantic-Segmentation-T3P2
Semantic segmentation uses transposed convolutions in the decoder part to segment the images in classes. This projects implements a FCN8 architecture to detect the roads in the image.Vehicle-Detection-T1P5
This project used machine learning to train a classifier to classify cars in video and then draw bounding boxes around them. I used sliding window technique, and heat map to bind the car images in rectangles.Path-Planning-Project-T3P1
Prediction, behaviour planning and trajectoryLove Open Source and this site? Check out how you can help us