abidrahmank

import numpy as np
import cv2
import time,sys,os

ply_header = '''ply
format ascii 1.0
element vertex %(vert_num)d
property float x
property float y
property float z

abidrahmank

import numpy as np
import cv2
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import axes3d

FLANN_INDEX_KDTREE = 0
index_params = dict(algorithm = FLANN_INDEX_KDTREE, trees = 5)
search_params = dict(checks = 50)
flann = cv2.FlannBasedMatcher(index_params, search_params)

abidrahmank

import cv2
import numpy as np

from matplotlib import pyplot as plt


def drawlines(img1,img2,lines,pts1,pts2):
    ''' img1 - image on which we draw the epilines for the points in img1
        lines - corresponding epilines ''' 
    r,c = img1.shape

abidrahmank

import cv2
import numpy as np

from matplotlib import pyplot as plt


def drawlines(img1,img2,lines,pts1,pts2):
    ''' img1 - image on which we draw the epilines for the points in img1
        lines - corresponding epilines ''' 
    r,c = img1.shape

abidrahmank

In [8]: %prun single_process(contours)
         6000013 function calls in 39.007 seconds

   Ordered by: internal time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
  3000000   36.424    0.000   36.424    0.000 {cv2.pointPolygonTest}
        1    2.056    2.056   39.006   39.006 pointpolygontest.py:18(single_process)
  3000000    0.514    0.000    0.514    0.000 {method 'itemset' of 'numpy.ndarray' objects}
        4    0.010    0.002    0.010    0.002 {numpy.core.multiarray.zeros}

abidrahmank

import cv2,time
import numpy as np
from multiprocessing.pool import ThreadPool

img = cv2.imread('img2.png',0)


ret,src = cv2.threshold(img,127,255,0)
contours,hierarchy = cv2.findContours(src,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)

abidrahmank

.model C,flat

.data

.code

;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;
;  			MMX ASSEMBLY
;

abidrahmank

>>> centroids
[[98, 325], [232, 309], [472, 294], [96, 192], [453, 167], [84, 66], [445, 46]]

>>> match_pts
[[84, 310], [208, 310], [456, 310], [84, 188], [456, 188], [84, 66], [456, 66]]

abidrahmank

>>> centroids
[[329, 894], [463, 878], [703, 863], [327, 761], [684, 736], [315, 635], [676, 615]]
>>> sorted(centroids,key = lambda s:sum)
[[329, 894], [463, 878], [703, 863], [327, 761], [684, 736], [315, 635], [676, 615]]
>>> 

abidrahmank

#include <iostream>
using namespace std;

struct MyStruct 
{ 
int x;
};

void updateStruct (MyStruct my_struct)
{