Mayank Singh Rathore's Projects
the holistic detection detects face mesh ,hands and body postures.It can detect upto 30+fps.the project contains two different files one for 3d image detection and second for holistic detection. The project utilizes OpenCv, Python, MediaPipe API'S for detection.
It utilizes open cv, TensorFlow, and Keras to traindata.This project is built using opencv and python on pycharm. Training of data utilizes CNN generated usingTensorFlow and Keras.
about three thousand images were used for training CNN.It utilized opencv,NumPy,panda,imaging,Keras, TensorFlow,socketio,as major libraries.the neural network worked well on the first track.the model file stored the trained model.elu and softmax activation functions were employed.It can work on workstations without GPU but takes a considerable amount of time.
Devsnest internship program
this firebase chat app allows users to chat about a particular event that is currently hosted. The organizer has to just change the event.
A robot powered training repository :robot:
a multi blogging website where users can stay anonymous and express themselves.
This project uses NLTK(Natural Language Tool Kit),NLP(Natural Language Processing) and newspaper3k for sentiment analysis and news generation.
This project utilizes OpenCV, Python, and Mediapipe API to create a face mesh.It is capable of detecting face mesh and up to 100+ FPS(frames per second).It can easily run on workstations without GPU.
This project is build on pycharm using python and OpenCv .. It utilizes NLP and mediapipe face detection API. It is capable of detecting faces, frames per second(fps) and has a confidence threshold of 0.7.
this simple react app allows users to post photos in a gallery and contribute.The link of this app is---https://photograph-af70f.web.app/
this project is built using opencv and python on pycharm.It is capable of detecting edges and moment from a given video.
this project can increase the readability of a blurred page.It utilizes OpenCV and Python.
This computer vision project uses opencv, python,face-recognition, cmaker, and dlib packages to complete. It is capable of real-time video capture that it uses to match photos. As the match is completed it gives registers the name and time in a csv file. First photos are converted from RGB to BGR.
Example Streamlit app that you can fork to test out share.streamlit.io
Working Links for:--project1: https://quilled-zinc-carp.glitch.me --project2:https://oil-zesty-drip.glitch.me