This GitHub project is a curated collection of Python projects leveraging OpenCV and YOLOv8 for computer vision applications, including fingerprint matching and face recognition. It serves as both a learning resource for OpenCV basics and a showcase of advanced techniques in computer vision.
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OpenCV Basics: The fundamental concepts and operations in OpenCV
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QR & Barcode Detection: Identify and read QR codes and barcodes off images and videos
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Document Scanner: Digitizing physical documents into digital images and extracting the text
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Colorize Images: Colorize Black & White Images using a Deep neural network
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Motion Detection System: Detect and alert on movement in a video feed
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Parking Space Counter: Count available parking spaces in a parking lot
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Number Plate Recognition: Identify and read vehicle registration numbers
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Car Counter: Count cars that are passing by in a video feed
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Feature Detection: Identify game covers in a video stream using feature extraction
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Fingerprint Matching: Biometric technique using computer vision to compare fingerprints for authentication purposes
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Face Detection: Identify human faces in images and video feeds
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Face Recognition: Biometric technique using computer vision to identify or verify a person by analyzing patterns based on the person's facial features
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Review Sentiment Analysis: Analyze sentiment in amazon reviews using VADER / Roberta / Huggingface Pipeline
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Stock News Sentiment Analysis: Crawl and analyze sentiment in stock news headlines from finviz
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Stock Price Prediction: Download stock data and predicts stock price using machine learning with the LTSM model.
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Spam Detection: Detect spam texts using machine learning with the Naive Bayes algorithm
- Python 3.9 (or higher)
- pip
- Clone the repository to your local machine:
git clone https://github.com/0xBitBuster/python-projects
- Open up any project
- Install the required packages:
pip install -r requirements.txt