Description
Computer Vision Toolbox is a comprehensive solution for designing and testing computer vision systems. It offers a wide range of algorithms and apps for tasks such as visual inspection, object detection, and feature detection, extraction, and matching. The toolbox supports AI techniques including pretrained convolutional neural networks (CNNs), vision transformers, and vision-language models. These models can be used for image classification, object detection, segmentation, pose estimation, captioning, and optical character recognition (OCR). Additionally, the toolbox provides zero-shot models for tasks like optical flow and 3D depth estimation.
The toolbox includes tools for automating ground truth labeling with the Video Labeler and Image Labeler apps, which support object detection, semantic segmentation, instance segmentation, and scene classification. Camera calibration capabilities are also available, allowing for calibration workflows for single, fisheye, stereo, and multi-camera configurations.
For 3D vision applications, the toolbox supports stereo vision, structure from motion, neural radiance fields (NeRF), and real-time visual and point cloud SLAM. It also offers lidar and point cloud processing capabilities, enabling segmentation, clustering, downsampling, denoising, registration, and fitting of geometrical shapes.
Code generation is another key feature, with support for generating C, C++, and CUDA code for GPU execution, as well as hardware description languages (HDL) for rapid prototyping and deployment. The toolbox integrates with MATLAB and Simulink, allowing for seamless integration of OpenCV-based projects and functions.
Computer Vision Toolbox is ideal for engineers and researchers working on computer vision applications across various industries, including manufacturing, robotics, and autonomous systems. It provides a robust platform for developing and deploying advanced computer vision solutions.
Computer Vision Toolbox's Core Features
Pretrained CNNs and vision transformers
Automated ground truth labeling
Camera calibration for multiple configurations
3D vision support including SLAM
Lidar and point cloud processing
Code generation for C, C++, CUDA, and HDL
Integration with MATLAB and Simulink
Automated visual inspection library
How to use Computer Vision Toolbox?
Configure: Set up your computer vision system
Use: Apply algorithms for detection and segmentation
Optimize: Customize models through transfer learning
Deploy: Generate code for rapid prototyping
Computer Vision Toolbox's Use Cases
- Visual Inspection
- Object Detection
- 3D Vision Applications
- Lidar Processing
- Camera Calibration
