How to filter numpy array by list of indices?
It looks like you just need a basic integer array indexing: filter_indices = [1,3,5] np.array([11,13,155,22,0xff,32,56,88])[filter_indices]
nearest-neighbor
Rotate an image in C++ without using OpenCV functions
First, I have to admit I agree with generic_opto_guy: The approach with the loop looks good, so we would need to check the math. On thing I noticed: if (oldRow > 0 && oldCol > 0 && oldRow <= oldHeight && oldCol <= oldWidth) implies you start indexing with 1. I belife that opencv starts … Read more
Nearest-neighbor interpolation algorithm in MATLAB
This answer is more explanatory than trying to be concise and efficient. I think gnovice‘s solution is best in that regard. In case you are trying to understand how it works, keep reading… Now the problem with your code is that you are mapping locations from the input image to the output image, which is … Read more
How to understand Locality Sensitive Hashing? [closed]
The best tutorial I have seen for LSH is in the book: Mining of Massive Datasets. Check Chapter 3 – Finding Similar Items http://infolab.stanford.edu/~ullman/mmds/ch3a.pdf Also I recommend the below slide: http://www.cs.jhu.edu/%7Evandurme/papers/VanDurmeLallACL10-slides.pdf . The example in the slide helps me a lot in understanding the hashing for cosine similarity. I borrow two slides from Benjamin Van … Read more
Millions of 3D points: How to find the 10 of them closest to a given point?
Million points is a small number. The most straightforward approach works here (code based on KDTree is slower (for querying only one point)). Brute-force approach (time ~1 second) #!/usr/bin/env python import numpy NDIM = 3 # number of dimensions # read points into array a = numpy.fromfile(‘million_3D_points.txt’, sep=’ ‘) a.shape = a.size / NDIM, NDIM … Read more
Nearest neighbors in high-dimensional data?
I currently study such problems — classification, nearest neighbor searching — for music information retrieval. You may be interested in Approximate Nearest Neighbor (ANN) algorithms. The idea is that you allow the algorithm to return sufficiently near neighbors (perhaps not the nearest neighbor); in doing so, you reduce complexity. You mentioned the kd-tree; that is … Read more