ML driven autopilot car

Description

Machine learning logics are written on Python using Tensorflow and Keras libraries for models operation and OpenCv for Computer Vision image preprocessing and objects detection. Input preprocessing I process the input image from the car into Canny-edges, Black-and-white, resized and depth images. I also find contours and search for objects in a frame. These data are fed into the neural network for more approximate calculation of the decision.

Machine learning logics are written on Python using Tensorflow and Keras libraries for models operation and OpenCv for Computer Vision image preprocessing and objects detection. Input preprocessing I process the input image from the car into Canny-edges, Black-and-white, resized and depth images. I also find contours and search for objects in a frame. These data are fed into the neural network for more approximate calculation of the decision.

Machine learning logics are written on Python using Tensorflow and Keras libraries for models operation and OpenCv for Computer Vision image preprocessing and objects detection. Input preprocessing I process the input image from the car into Canny-edges, Black-and-white, resized and depth images. I also find contours and search for objects in a frame. These data are fed into the neural network for more approximate calculation of the decision.

Machine learning logics are written on Python using Tensorflow and Keras libraries for models operation and OpenCv for Computer Vision image preprocessing and objects detection. Input preprocessing I process the input image from the car into Canny-edges, Black-and-white, resized and depth images. I also find contours and search for objects in a frame. These data are fed into the neural network for more approximate calculation of the decision.