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A software pipeline to identify the lane boundaries in a road using a combination of advanced techniques like gradient, color and perspective transforms along with distortion correction and camera calibrations.
This repository allows you to get started with a gui based training a State-of-the-art Deep Learning model with little to no configuration needed! Training with TensorFlow has never been so easy.
Utilize a kalman filter to estimate the state: position_x, position_y, velocity_x,velocity_y of a moving object of interest with noisy lidar and radar measurements.
In this project we utilize an Unscented Kalman Filter to estimate the state position_x,position_y, velocity, yaw,yaw_rate of a moving object of interest with noisy lidar and radar measurements.
Segmenting various features of the road to make it easier for self-driving cars to take decisions by using image processing techniques and a U-Net Neural Network
In this project, a lane line detection algorithm is developed in Python to detect curvature lane lines and the within lane region in videos shot by front facing camera in car.