Barcode-QR and Vehicle detection using YOLOv8
This project implements a web application for detecting barcodes, QR codes, and vehicles in images using YOLOv8 models. The models have been trained separately using the Ultralytics YOLO framework.
Features
Model Selection: Choose between barcode/QR code detection and vehicle detection.
Upload Image: Upload an image containing objects for detection.
Detection: Run detection on the uploaded image.
Results Display: View the detection results directly on the web interface.
URL:-Application
URL:- GitHub Repository
Brain tumor detection using Deep Learning
This brain tumor detection, classification, and diagnosis system with high accuracy (95%) that uses state-of-the-art Deep Learning methods.
In this proposed model, a pre-trained CNN architecture is employed for the classification that uses many labeled images for training the model obtained from large-scale datasets like ImageNet and Kaggle.
URL:- GitHub Repository
Sign language to speed application
Project Name Sign language to speech with multiple languages
The problem it solves With the help of our application, deaf-dumb people can easily communicate with common people. Our app converts sign language to speak 18 different languages which include 8 Indian languages.
WHAT CAN PEOPLE USE IT FOR, OR HOW IT MAKES EXISTING TASKS EASIER/SAFER
Our application provides an easy medium to connect deaf-dumb people and common people. It converts sign language to text and speech and also provides features of multiple languages for output. For example, I am someone who only understands the Tamil language. With the help of this application, I can understand sign language because the application will convert sign language into Tamil text and speech output.
Challenges we ran into We faced one hurdle in how to detect sign language accurately. We used "resnet50" a pre-trained model to solve that hurdle. We train our machine-learning model with a large dataset to achieve high accuracy.
Technologies we used TensorFlow lite Android Studio Java Python Extensible Markup Language Computer Vision(Open CV) Natural Language Processing
URL:- GitHub Repository
Video:-Demo
Stock market crash prediction web application
Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code).
The front end of the Web App is based on Flask and WordPress.
The App forecasts stock prices for the next seven days for any given stock under NASDAQ or NSE as input by the user.
Predictions are made using three algorithms: ARIMA, LSTM, and Linear Regression.
The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendations on whether the price is going to rise or fall.
URL: GitHub Repository