Obviously Awesome

My GitHub code

Image dataset utilities
1. Stereo images
2. LFW (labeled faces in the wild)
3. Selected scientific images
4. Selected general-purpose images
Numpy ops
1. Simple example
2. Block views
Edges & Lines
1. Finding contours
2. Convex hulls (binary images)
3. Canny filters
4. Marching cubes
5. Ridge finders
6. Active contour model
7. Drawing standard shapes
8. Drawing random shapes
9. Hough transform (straight line detector)
10. Polygon approximation & subdivision
11. Hough transform (circular & elliptical)
12. Skeletonizer
13. Edge Operations
Image & Feature Detection
1. DAISY local image descriptor
2. HOG (histogram of oriented gradients)
3. Template matching (image patch ID)
4. Corner detection
5. Hole filling
6. Peak detection
7. CENSURE (feature detection)
8. MB-LBP (multiblock local binary pattern - texture classification)
9. HAAR (feature descriptors)
10. Blob detection - LoG, DoG, DoH
11. ORB feature detection
12. BRIEF binary descriptor
13. Gabor filters
14. GLCM (gray level co-occurence matching - texture classification)
15. Shape indexing (curvature measure)
16. Sliding window histograms (object detection)
17. Gabor filter banks (texture classification)
18. LBP (local binary pattern - texture classification)
Filtering & Restoration
1. Hysteresis thresholding
2. Image deconvolution
3. Mean filters (local, percentile, bilateral)
4. Unsharp masking (image sharpening)
5. Richardson-Lucy image deconvolution
6. Inpainting
7. Entropy filters
8. Denoising (3 filter types)
9. Shift-invariant wavelet denoising
10. Phase unwrapping
11. Non-local means denoising (texture preservation)
12. Attribute operators (contour preservation filters)
13. Wavelet denoising
Transforms & Registration
1. Swirl
2. Image pyramids
3. Interpolation: edge modes
4. Rescale / Resize / Downscale
5. Piecewise affine transforms
6. Structural similarity index
7. Phase correlation
8. FM (fundamental matrix) estimation
9. Masked, normalized cross-correlation
10. Polar & log-polar transforms
11. Line model estimation with RANSAC
12. Radon transforms
13. Image matching with RANSAC
Exposures & Color Channels
1. RGB to grayscale
2. RGB to HSV (hue/saturation/value)
3. Histogram matching
4. Color separation
5. Grayscale filters & RGB images
6. Filtering regional maxima (bright features)
7. Local histogram equalization (LHE)
8. Gamma & log-contrast adjustments
9. Histogram equalization
10. Tinting grayscale images
Object Segmentation
1. RAGs - region boundary basis
2. Normalized cuts
3. RAG thresholding
4. Watershed transforms
5. RAG drawing
6. Thresholding (binary from grayscale)
7. Chan-Vese segmentation
8. Finding local maxima
9. Niblack & Sauvola thresholding
10. Multi-otsu thresholding
11. Labeling image regions
12. Measuring region properties
13. Random walker segmentation
14. Watershed segmentation
15. Watershed markers
16. Segmenation vs Superpixel algorithms
17. Finding intersection of 2 segmentations
18. RAGs - mergenodes function
19. RAG merging
20. RAGs - hierarchical merging
21. Local extrema
22. Flood filling
23. Morphological snakes
24. Metrics
Additional Examples
1. LI thresholding
2. Max-tree (hierarchical image representation)