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This repository uses OpenCV, Python and NumPy to create a project that focuses on detecting and prioritizing red and blue houses in aerial images, distinguishing between those that are on fire (brown areas) and those that are safe on grass (green areas). Using OpenCV and Python, the program then assigns rescue priority to different locations .
This code when executed via a terminal allows user to take a snapshot via OpenCV, convert it into grayscale and store it in desired folder. This is useful for capturing images via a computer for machine learning datasets.
OpenCV é a principal biblioteca de código aberto para a visão computacional, processamento de imagem e aprendizagem de máquina, apresenta também a aceleração de GPU para operação em tempo real. Aqui vai uma demonstração da biblioteca, além de um tutorial curto para nosso aprendizado.
Computer Vision, often abbreviated as CV, is defined as a field of study that seeks to develop techniques to help computers “see” and understand the content of digital images such as photographs and videos.
This Python script downloads YouTube videos and extracts unique frames, creating two PDFs: Frames PDF: A PDF containing unique frames from the video, each labeled with its timestamp. Transcript PDF: A PDF with the video transcript, synchronized with the frame timestamps.