Description

Computer Vision Toolkit is an ideal starting point for beginners in the field of computer vision. This toolkit comprises various Python scripts, leveraging OpenCV, to cover fundamental computer vision topics. Each script is meticulously commented and user-friendly, ensuring a thorough understanding of each concept. Highlights of this toolkit include:

• Mono and Stereo Calibration: Exploring calibration using chessboard and charuco patterns, with detailed guidance for both mono and stereo systems.
• Distortion Removal: Providing scripts for lens distortion removal, crucial for enhancing image quality for advanced processing.
• Parameter Determination: Offering methodologies to calculate key parameters such as baseline, field of view, and focal length.
• Image Rectification in Stereo Systems: Detailing procedures for rectifying images in stereo camera setups to align images for depth analysis.
• Disparity and Depth Maps Generation: Techniques to generate disparity maps for depth estimation and depth maps creation from stereo images.
• Distance Measurement from Images: Methods for measuring distances in images using maps, illustrated with practical examples.
• Point Cloud Generation and 3D Visualization: Tools and scripts to generate point clouds from stereo images and visualize them in 3D.
• Optical Flow from Video Files: Implementing optical flow algorithms on video data to analyze object movement across frames.

Additionally, the toolkit features a variety of example tasks accompanied by resource files to further practice and refine computer vision skills. It also includes a user-friendly API packed with functionalities essential for the tasks mentioned, ensuring a smooth learning journey.