berak

/*M///////////////////////////////////////////////////////////////////////////////////////
//
//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
//  By downloading, copying, installing or using the software you agree to this license.
//  If you do not agree to this license, do not download, install,
//  copy or use the software.
//
///*M///////////////////////////////////////////////////////////////////////////////////////
//

berak

import cv2
import numpy as np
import tensorflow as tf
import tensorflow.examples.tutorials.mnist.input_data as input_data

def init_weights(shape):
    return tf.Variable(tf.random_normal(shape, stddev=0.01))


def model(X, w_h, w_o):

berak

'''
A Reccurent Neural Network (LSTM) implementation example using TensorFlow library.
This example is using the MNIST database of handwritten digits (http://yann.lecun.com/exdb/mnist/)
Long Short Term Memory paper: http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf
Author: Aymeric Damien
Project: https://github.com/aymericdamien/TensorFlow-Examples/
'''
import cv2
import tensorflow as tf
import tensorflow.examples.tutorials.mnist.input_data as input_data

berak

# Copyright 2015 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

berak

import cv2
import numpy as np
import tensorflow as tf


def asRow(X):
    """
    Creates a row-matrix from multi-dimensional data items in list l.
    
    X [list] List with multi-dimensional data.

berak

#include "opencv2/opencv.hpp"
using namespace cv;

#include <iostream>
using namespace std;

//
// b g r y cr cb h s v like pearls ona string.
//
Mat feature(const Vec3b &pixel) {

berak

#include "opencv2/opencv.hpp"
#include <iostream>
using namespace cv;
using namespace std;

Mat im_hsv;
void pick_color(int e, int x, int y, int s, void *)
{
    if (e==1)
    {

berak

// http://answers.opencv.org/moderation-queue/

var inp = document.getElementsByTagName("input")
 
for (i=0; i<inp.length; i++) {
  if (inp[i].type == "checkbox") {
    inp[i].checked = true;
  }
}

berak

namespace ROC {
    void curve(const Mat &probs, const Mat &truth, vector<Point2f> &roc, int N, const float eps=1e-1) {
        for (int i=0; i<N; i++) {
            float thresh = float(N-i) / N;
            float TP = countNonZero((probs >  thresh) & (truth >  eps));
            float TN = countNonZero((probs <= thresh) & (truth <= eps));
            float FP = countNonZero((probs >  thresh) & (truth <= eps));
            float FN = countNonZero((probs <= thresh) & (truth >  eps));
            float FPR = FP / (FP + TN);
            float TPR = TP / (TP + FN);

berak

#include <opencv2/opencv.hpp>
#include <iostream>
#include <deque>
#include <map>
using namespace cv;
using namespace std;


int main(int argc, char **argv)
{