ArrowsΒΆ
Arrows is the collection of plugins that provides implementations of the algorithms declared in Vital. Each arrow can be enabled or disabled in build process through CMake options. Most arrows bring in additional third-party dependencies and wrap the capabilities of those libraries to make them accessible through the Vital APIs. The code in Arrows also converts or wrap data types from these external libraries into Vital data types. This allows interchange of data between algorithms from different arrows using Vital types as the intermediary.
Best practices for dealing with some specific details in arrows is available in the Arrows Coding Patterns.
Capabilities are currently organized into Arrows based on what third party library they require. However, this arrangement is not required and may change as the number of algorithms and arrows grows. Some arrows, like core, require no additional dependencies.
The provided Arrows are:
- Core
- Class Probablity Filter Algorithm
- Close Loops Bad Frames Only Algorithm
- Close Loops Exhaustive Algorithm
- Close Loops Keyframe Algorithm
- Close Loops Multi Method Algorithm
- Compute Ref Homography Core Algorithm
- Convert Image Bypass Algorithm
- Detected Object Set Input csv Algorithm
- Detected Object Set Input kw18 Algorithm
- Detected Object Set Output csv Algorithm
- Detected Object Set Output kw18 Algorithm
- Dynamic Config None Algorithm
- Estimate Canonical Transform Algorithm
- Example Detector Algorithm
- Feature Descriptor I/O Algorithm
- Filter Features Magnitude Algorithm
- Filter Fatures Scale Algorithm
- Filter Tracks Algorithm
- Formulate Query Core Algorithm
- Hierarchical Bundle Adjust Algorithm
- Initialize Cameras Landmarks Algorithm
- Match Features Fundamental Matrix Algorithm
- Match Features Homography Algorithm
- Track Descriptor Set Output csv Algorithm
- Track Features Core Algorithm
- Frame Index Track Set Class
- Triangulate Landmarks Algorithm
- Video Input Filter Algorithm
- Video Input Image_list Algorithm
- Video Input Pos Algorithm
- Video Input Split Algorithm
- Burnout
- Ceres
- Darknet
- Matlab
- OpenCV
- Analyze Tracks Algorithm
- Detect Features Algorithm
- Detect Features AGAST Algorithm
- Detect Features FAST Algorithm
- Detect Features GFTT Algorithm
- Detect Features MSD Algorithm
- Detect Features MSER Algorithm
- Detect Features Simple BLOB Algorithm
- Detect Features STAR Algorithm
- Draw Detected Object Set Algorithm
- Draw Tracks Algorithm
- Estimate Fundamental Matrix Algorithm
- Estimate Homography Algorithm
- Extract Descriptors Algorithm
- Extract Descriptors BRIEF Algorithm
- Extract Descriptors DAISY Algorithm
- Extract Descriptors FREAK Algorithm
- Extract Descriptors LATCH Algorithm
- Extract Descriptors LUCID Algorithm
- Extrack Descriptors BRISK Algorithm
- Detect Features BRISK Algorithm
- Extrack Descriptors ORB Algorithm
- Detect Features ORB Algorithm
- Extrack Descriptors SIFT Algorithm
- Detect Features SIFT Algorithm
- Extrack Descriptors SURF Algorithm
- Detect Features SURF Algorithm
- Hough Circle Detector Algorithm
- Image Container Algorithm
- Image I/O Algorithm
- Match Features Algorithm
- Match Features Bruteforce Algorithm
- Match Features Flannbased Algorithm
- Refine Detections Write To Disk Algorithm
- Split Image Algorithm
- Proj4
- UUID
- VisCL
- VXL
- Bundle Adjust Algorithm
- Camera Map Class
- Close Loops Homography Guided Algorithm
- Compute Homography Overlap
- Estimate Canonical Transform Algorithm
- Estimate Essential Matrix Algorithm
- Estimate Fundamental Matrix Algorithm
- Estimate Homography Algorithm
- Estimate Similarity Transform Algorithm
- Image Container Class
- Image I/O Algorithm
- Match Features Constrained Algorithm
- Optimize Cameras Algorithm
- Vital to VXL Algorithm
- VXL to Vital Algorithm
- Split Image Algorithm
- Triangulate Landmarks Algorithm
- FFmpeg Video Input Algorithm
- Image Memory Class
- Image Memory Chunk Class