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advance_lane_line_detection

here i used combination of filters for images like hls, sobel x and y, grayscale, hsv etc to make the lane lines clearly identifiable. Afterwards i used trapezoidal area to select my region of interest and used best fit to fine the lane lines. Even with shadows and different light conditions lane lines can be detected here.

behavioral-_cloning-traffic_sing_classifier

I used machine learning techniques, deep learning, neural network and convolution to make a deep neural network classifier to classify traffic signs. I took data from german sign boards. My test sample data set accuracy is 95%.

brickbreaker

a java coded game of breaking bricks by ball and maintaining balance of ball on a slider

carbon

A design system built by IBM

carbon-components-angular

An Angular implementation of the Carbon Design System for IBM.

codfod

graphql

lane_lines_detection

movie-search

namaste-react

namaste-react-restart

netflix-gpt

profiles-rest-api

react-micro-frontend

react-notes

recipe-app-api

recipe-app-api django rest framework source code

scs

shopping-cart-react

spychat

suhana-safar

tour

try

twitter-boat

vanilla-javascript

viberr

Viberr is a music webiste made in django/python

wordigo