e2evideo package

This webpage with its subpages provides a tutorial for the e2evideo pacakge. It has three main modules:

Video Preprocessing

This module provides functionality for extracting frames from videos, including reading videos from a specified directory, creating an output folder, and saving frames according to the specified sampling mode. The tutorial explains the dependencies required, the parameters for the main() function, and provides example usage from the command line and within another Python script. This module is useful for preprocessing video data for machine learning tasks.

Image Preprocessing

This module provides functionality for reading and preprocessing images, including resizing, converting to grayscale, reading from a specified directory, and saving processed images as NumPy arrays. It also saves the labels of images. The tutorial explains the dependencies required, the parameters for the get_images() function, and provides example usage from the command line and within another Python script. This module is useful for preprocessing image data for machine learning tasks.

Feature Extractor

This module is used for extracting features from images using a Convolutional Autoencoder (CAE). The tutorial explains the dependencies required, the parameters for the main() function, and provides example usage from the command line and within another Python script. The main() function can either train a CAE using a given training set or load a pre-trained model and use it to generate and plot features for a set of test images. This module is useful for extracting features from image data for machine learning tasks.

^* This tutorial has been made with the help of ChatGPT 4.0.