Omkar Bhalerao's repositories
Self-Driving-Car
A scaled down version of the self-driving system using OpenCV. The system comprises of - • Raspberry Pi with a webcam and an ultrasonic sensor as inputs, ◦ Steering using move in sdcar.py ◦ Stop sign detection using houghcircles and colour intensities ◦ Front collision avoidance using an ultrasonic sensor • l298N motor controller • project structure: *sdcar.py is a combination of all the following *lane_lines.py: step1.take the webcam feed and apply the canny edge algorithm to detect the edges step2. detect the lines in an edged image using houghlines step3. average the lines according to the slope step4.making points using slope step5. return right, left, camera and central line *sensor.py: distance measurement using input and output pins *sign.py: *detection of circles in image using hough circles *if the dominant colour in a square region around the circle is red then it is stop sign. *if the dominant colour in a square region around the circle is blue then there are 5 cases left, right, forward, forward and right or forward and left for this: • make the 3 zones of square regions the right , left, upper(for forward) • if the right zone is white and the other two are blue then the sum of RGB colour intensities in the right zone will be obviously greater than the other two zones then the sign is right similarly for others. Note : sign.py will work on following type of sign:
Medium-Article-Manim
Manim code for medium article (univ approx theorem)
Course-Materials
Course Files
CS224N-Stanford-Winter-2019
The collection of ALL relevant materials about CS224N-Stanford/Winter 2019 course. THANKS TO THE PROFESSOR AND TAs! 斯坦福大学CS224N 【2019】课程的【所有】相关的资料。感谢Chris Manning教授和Abigail See，感谢所有助教！
Hackathons
Submission to various hackathons
Lab-Based-Project
Lab Based Project (Backorder Prediction)
Paper-Summaries
Summaries of few read papers
stats-learning-notes
Notes from Introduction to Statistical Learning