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rgbcube.m下载
function rgbcube(vx,vy,vz)
vertices_matrix = [0 0 0;0 0 1;0 1 0;0 1 1;1 0 0;1 0 1;1 1 0;1 1 1];
faces_matrix = [1 5 6 2;1 3 7 5;1 2 4 3;2 4 8 6;3 7 8 4;5 6 8 7];
colors = vertices_matrix;
patch('Vertices',vertices_matrix,'Faces',faces_matrix,'FaceVertexCData',colors,'FaceColor','interp','EdgeAlpha',0);
%set up viewing point
2018-05-22
imnoise3.m
function [r,R,S] = imnoise3(M, N, C, A, B)
K =size(C, 1);
if nargin < 4
A = ones(1,K);
end
if nargin < 5
B = zeros(K, 2);
end
R = zeros(M, N);
2018-05-21
reader.py下载
# -*- coding: utf-8 -*-
"""
Created on Mon May 7 19:43:04 2018
@author: Administrator
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import collections
import tensorflow as tf
import os
import numpy as np
def _read_words(filename):
with tf.gfile.GFile(filename, "r") as f:
return f.read().replace("\n", "").split()
def _build_vocab(filename):
data = _read_words(filename)
counter = collections.Counter(data)
count_pairs = sorted(counter.items(), key=lambda x: (-x[1], x[0]))
words, _ = list(zip(*count_pairs))
word_to_id = dict(zip(words, range(len(words))))
return word_to_id
2018-05-21
statmoments.m
function [v,unv]=statmoments(p,n)
% STATMOMENTS Computes statistical central moments of image histogram.
% [v,unv]=statmoments(p,n) computes up to the Nth statistical
% central moment of a histogram whose components are in vector
% P. The length of must equal 256 or 65536.
% ****from ggbondg****
% The program outputs a V with V(1)=mean, V(2) = variance.
% V(3) = 3rd moment,...V(N)=Nth central moment. The random
% variable values are normalized to the range [0,1], so all
% moments also are in this range.
% ****from ggbondg****
% The program also outputs a Vector UNV containing the same moments
% as V,but using un-normalized random variable values (e.g., 0 to
% 255 if length(P)=2^8). For example, if length(P)=256 and V(1)
% = 0.5, then UNV(1) would have the value UNV(1)=127.5 (half of
% the [0 255] range).
%****from ggbondg****
2018-05-21
imnoise2.m
function R = imnoise2(type, varargin)
%IMNOISE2 Generates an array of random numbers with specified PDF.
% R = IMNOISE2(TYPE, M, N, A, B) generates an array, R, of size
% M-by-N, whose elements are random numbers of the specified TYPE
% with parameters A and B. If only TYPE is included in the
% input argument list, a single random number of the specified
% TYPE and default parameters shown below is generated. If only
% TYPE, M, and N are provided, the default parameters shown below
% are used. If M = N = 1, IMNOISE2 generates a single random
% number of the specified TYPE and parameters A and B.
%
% Valid values for TYPE and parameters A and B are:
%
% 'uniform' Uniform random numbers in the interval (A, B).
% The default values are (0, 1).
% 'gaussian' Gaussian random numbers with mean A and standard
% deviation B. The default values are A = 0, B = 1.
% 'salt & pepper' Salt and pepper numbers of amplitude 0 with
% probability Pa = A, and amplitude 1 with
% probability Pb = B. The default values are Pa =
% Pb = A = B = 0.05. Note that the noise has
% values 0 (with probability Pa = A) and 1 (with
% probability Pb = B), so scaling is necessary if
% values other than 0 and 1 are required. The noise
% matrix R is assigned three values. If R(x, y) =
% 0, the noise at (x, y) is pepper (black). If
% R(x, y) = 1, the noise at (x, y) is salt
% (white). If R(x, y) = 0.5, there is no noise
% assigned to coordinates (x, y).
% 'lognormal' Lognormal numbers with offset A and shape
% parameter B. The defaults are A = 1 and B =
% 0.25.
% 'rayleigh' Rayleigh noise with parameters A and B. The
% default values are A = 0 and B = 1.
% 'exponent
2018-05-21
dftfilt.m下载
function g = dftfilt(f,H)
% 此函数可接受输入图像和一个滤波函数,可处理所有的
% 滤波细节并输出经滤波和剪切后的图像
% 将此.m文件保存在一个文件夹
% file->set path->add with subfolder
% 将你函数所在文件夹添加到搜索路径
% save就可以将其添加到你的函数库了
2018-05-21
adpmedian.m
function f = adpmedian(g, Smax)
if(Smax <=1) || (Smax/2 ==round(Smax/2)) || (Smax ~= round(Smax))
error('SMAX must be an odd integer >1.')
end
% Initial setup
f = g;
f(:) = 0;
alreadyProcessed = false(size(g));
% Begin filtering.
2018-05-21
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