Gokul Raj's repositories
cats-api
REST API with NodeJs, Typescript, Express.js and Sequelize with Sqlite3 |CRUD REST API
pets-api
A Pet API is an Application Programming Interface which developers can use to retrieve data about pets and use it to enhance their own applications.
json-blog
A react app that provides a simple blog website using JSON server for Mock APIs with CRUD Functionality
stopwatch-and-countdowntimer
A PWA react application hosted on netlify that has features like stopwatch and countdown timer
git-commands
Sample app for learning git commands
cryptoverse
React Deployed at AWS-AMPLIFY.
Noblesse
react application that showcases the nobel prize winners for the last 100 years.
SocioInk-Frontend
SocioInk Frontend created using react, redux, material ui, css , dayjs, busboy
SocioInk-backend
SocioInk backend created using Node JS, Express JS, Busboy, and Firebase functions
movie-recommender-system-using-python
using cosine similarity algorithm, the program recommends first 50 titles that is similar to the query title , with respect to the dataset file in the form of a csv file.
UNO-Card-Recognition-and-Detection-using-CBIR
Two sets of data were collected for this project. One set is the training images [fig.1] used to develop the database from which the query image can be matched to. The other set is the images [fig.2] used to test the implementation. In this document, the first set is referred to as training or template images and the second set is referred to as target or test images.Both sets of images were collected with a Pixel 3 camera using the standard settings. In order to get a consistent performance, dark backgrounds were used in all of the images to ease in the card detection process. For the training images, 54 pictures were taken, one for each of the 54 different cards For this project, two approaches to detecting and identifying playing cards were explored. The first method uses feature detection with SIFT to find keypoints and descriptors and flann’s algorithm to show the matches between the key points in the target and the training images. The second approach uses orb algorithm to find keypoints and descriptors and brute force algorithm to show the matches.