text-to-speech-converter

touchless-user-interface-for-sketching-using-hand-gesture-recognition

The study presents a solution for a hand identification system for air application sketching. The experimental accuracy is 98.48 percent, which meets real-world requirements. Traditional writing and teaching approaches may be challenged by this system.

virtual-reality-air-drums-band-using-python

virtual_piano

volume-brightness-control-using-hand-gesture-using-python-and-opencv

The camera in our device is used for this project. It detects our hand with points in it so as it can see the distance between our thumb finger tip and index finger tip. The distance between the points 4 and 8 is directly proportional to the volume of device.OpenCV is short for Open Source Computer Vision. Intuitively by the name, it is an open-source Computer Vision and Machine Learning library. This library is capable of processing real-time image and video while also boasting analytical capabilities. It supports the Deep Learning frameworks. Building a Brightness Controller with OpenCV can be accomplished in just 3 simple steps: Step 1. Detect Hand landmarks Step 2. Calculate the distance between thumb tip and index finger tip. Step 3. Map the distance of thumb tip and index finger tip with volume range. For my case, distance between thumb tip and index finger tip was within the range of 15 - 220 and the volume range was from 0 - 100.It's same as Volume Control Using Hand Detection & Brightness Control Using Hand Detection. Only difference is now we can manage brightness with left hand & volume with right hand simultaneous.

web-design-in-tamil-learning-web-page

web_book_template

whatsappbot-using-python

System Requirements:

yawn-detection-using-machine-learning