Learn how to preprocess data for object detection in Python using OpenCV and scikit-image libraries. This article covers techniques such as image resizing, normalization, and data augmentation.
Official Python documentation provides an overview of object detection using Python, including data preprocessing steps such as loading images, converting to tensors, and applying transformations.
This online course covers data preprocessing techniques for computer vision tasks, including object detection. Learn how to handle image data, apply filters, and perform feature extraction using Python and OpenCV.
A step-by-step tutorial on object detection in Python using the YOLO algorithm. This guide covers data preprocessing, model training, and evaluation, with a focus on practical implementation.
Stanford University's CS231n course notes cover data preprocessing techniques for deep learning, including object detection. Learn about data augmentation, normalization, and feature scaling using Python and NumPy.
A video tutorial on object detection using Python and OpenCV. This video covers data preprocessing, model training, and object detection using the YOLO algorithm, with a focus on practical implementation.
An open-source tool for data preprocessing and object detection in Python. This tool provides a simple interface for loading images, applying transformations, and saving preprocessed data.
A research paper surveying object detection techniques in Python, including data preprocessing methods. This paper provides an overview of the current state of object detection research and future directions.