Custom implementations of common machine learning algorithms. Purely for training purposes and not intended for productive use.
All files can simply be executed with python filename.py (i.e. no command line arguments).
Computer Vision
- binary_dilation_erosion.py - Dilation, Erosion, Opening and Closing for binary images.
- canny.py - Canny edge detector.
- crosscorrelation_convolution.py - Implementation of crosscorrelation and convolution to apply filters to images.
- eigenfaces.py - Apply a PCA (from sklearn) to human faces, plot the principal components (aka eigenfaces).
- gauss.py - Gauss filter for smoothing of images.
- gradients.py - Calculate x and y derivatives of an image using symmetric, backward and forward gradient techniques.
- graph_image_segmentation.py - Split an image to segments using a simple graph based technique with internal and external subgraph differences.
- harris.py - Calculate the Harris edge detector score of pixels in an image.
- histogram_equalization.py - Normalize the intensity histogram of an image using histogram stretching and cumulative histogram equalization.
- hough.py - Find a line in a noisy image using a Hough Transformation.
- mean_shift_segmentation.py - Split an image to segments using mean shift clustering.
- otsu.py - Binarize an image using Otsu's method.
- prewitt.py - Apply a Prewitt filter to an image to calculate the x/y gradients.
- rank_order.py - Apply rank order filters to an image for (non-binary) erosion/dilation/closing/opening, median filtering and morphological edge detection.
- sift.py - Simplified implementation of the SIFT keypoint locator. Does not contain the descriptor nor sophisticated keypoint filtering (using hessian und principal curvatures). Also does not resize scales with higher sigmas.
- sobel.py - Apply a Sobel filter to an image for smoothed gradient calculation.
- template_matching.py - Find an example template image in a larger image.
Classifiers
- gaussian_mixture_1d_em.py - Train a mixture model of 1d gaussians using the EM algorithm.
Python 2.7, scipy, numpy, sklearn, scikit-image, matplotlib