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sharadgupta27 / compare-svm-kernels.py
Created January 30, 2018 07:28 — forked from WittmannF/compare-svm-kernels.py
Visualization of SVM Kernels Linear, RBF, Poly and Sigmoid on Python (Adapted from: http://scikit-learn.org/stable/auto_examples/classification/plot_classifier_comparison.html)
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
from sklearn.cross_validation import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.datasets import make_moons, make_circles, make_classification
from sklearn.svm import SVC
h = .02 # step size in the mesh
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sharadgupta27 / SFM.md
Created October 30, 2017 10:51 — forked from patriciogonzalezvivo/SFM.md
SfM Tools

VisualSFM by Changchang Wu

Probably the most straight forward way to start generating Point Clouds from a set of pictures.

VisualSFM is a GUI application for 3D reconstruction using structure from motion (SFM). The reconstruction system integrates several of my previous projects: SIFT on GPU(SiftGPU), Multicore Bundle Adjustment, and Towards Linear-time Incremental Structure from Motion. VisualSFM runs fast by exploiting multicore parallelism for feature detection, feature matching, and bundle adjustment.

For dense reconstruction, this program supports Yasutaka Furukawa's PMVS/CMVS tool chain, and can prepare data for Michal Jancosek's CMP-MVS. In addition, the output of VisualSFM is natively supported by Mathias Rothermel and Konrad Wenzel's [SURE]