Ashish ashish-kubade

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

	import numpy as np
	import numpy.linalg

	# Relevant links:
	# - http://stackoverflow.com/a/32244818/263061 (solution with scale)
	# - "Least-Squares Rigid Motion Using SVD" (no scale but easy proofs and explains how weights could be added)


	# Rigidly (+scale) aligns two point clouds with know point-to-point correspondences
	# with least-squares error.

	// A simple quickref for Eigen. Add anything that's missing.
	// Main author: Keir Mierle

	#include <Eigen/Dense>

	Matrix<double, 3, 3> A; // Fixed rows and cols. Same as Matrix3d.
	Matrix<double, 3, Dynamic> B; // Fixed rows, dynamic cols.
	Matrix<double, Dynamic, Dynamic> C; // Full dynamic. Same as MatrixXd.
	Matrix<double, 3, 3, RowMajor> E; // Row major; default is column-major.
	Matrix3f P, Q, R; // 3x3 float matrix.