YOLO YOLOv7 Applications

Browse applications built on YOLO YOLOv7 technology. Explore PoC and MVP applications created by our community and discover innovative use cases for YOLO YOLOv7 technology.

Stock Edge

Stock Edge is an innovative stock analysis platform that aims to empower investors with advanced analytical tools. It introduces the concept of utilizing time series analysis to unlock the power of stock analysis and forecasting, enabling users to make informed investment decisions. Stock Edge differentiates itself by offering precise predictions of future stock prices. By leveraging the power of time series analysis, it provides accurate forecasts that assist investors in understanding potential market movements. This feature is particularly valuable for investors who rely on data-driven strategies and seek to optimize their returns. StockEdge is able to uncover hidden patterns and trends in historical stock data. Through comprehensive analysis of large datasets, the platform enables investors to identify patterns that might not be apparent at first glance. This unique insight empowers investors to anticipate market movements and capitalize on emerging opportunities. The platform is designed to cater to a wide range of users, from seasoned investors to beginners. It offers a user-friendly interface and intuitive tools that make stock analysis accessible to everyone, regardless of their prior experience or expertise in financial markets. Informed decision-making is a central theme, as the platform provides timely and accurate insights that enable users to make real-time decisions based on market trends and potential risks. Additionally, Stock Edge aims to enhance financial performance by equipping users with the tools and information needed to optimize portfolio allocations and identify undervalued assets. Furthermore, Stock Edge envisions driving market innovation by democratizing access to sophisticated forecasting techniques. By making these advanced analytical tools available to a broader range of investors, the platform seeks to empower a new generation of investors to navigate complex market dynamics and contribute to positive change in the financial industry.

Hope
Streamlit
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YOLOv7

Egyptian Car Plate Recognition System

-License plate recognition is an important technology with many applications like electronic toll collection, traffic law enforcement, and vehicle tracking and identification. The goal of an LPR system is to automatically detect and extract the license plate number from an image or video of a car -License plate detection. YOLOv8 can be trained on a dataset of car images with labeled license plates to build a detection model. At runtime, it will take an input image, run the model, and return the coordinates of any license plates it finds -The license plate image can be extracted from the original image using the coordinates identified by YOLOv8. OpenCV functions like cropping and perspective transforms can prepare the license plate image for the next step -The license plate characters then need to be segmented into individual letters/digits. This involves techniques like morphological operations, contours, and character segmentation in OpenCV -Optical character recognition is used to identify each character. The segmented characters can be fed into a pretrained OCR model like Tesseract or a custom CNN model built with OpenCV and machine learning -The pipeline outputs the license plate text which can then be used for various applications. Building this system with OpenCV and YOLOv8 allows for fast, accurate, and robust license plate recognition in real-time. It has important uses in transportation, law enforcement, and security domains

AI Teem
EasyOCRYOLOv7