Metadata-Version: 2.1
Name: locate-pixelcolor-cpp-parallelfor
Version: 0.11
Summary: Detects colors in images up to 10 x faster than Numpy
Home-page: https://github.com/hansalemaos/locate_pixelcolor_cpp_parallelfor
Author: Johannes Fischer
Author-email: aulasparticularesdealemaosp@gmail.com
License: MIT
Keywords: cpp,c++,image,search,parallel,rgb
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Utilities
Description-Content-Type: text/markdown
License-File: LICENSE.rst
Requires-Dist: numpy

# Detects colors in images up to 10 x faster than Numpy 

### pip install locate-pixelcolor-cpp-parallelfor

#### Tested against Windows 10 / Python 3.10 / Anaconda

### Important!
The module imports a function from a compiled .dll (C++). 
If you get any import errors, install:  https://download.visualstudio.microsoft.com/download/pr/8b92f460-7e03-4c75-a139-e264a770758d/26C2C72FBA6438F5E29AF8EBC4826A1E424581B3C446F8C735361F1DB7BEFF72/VC_redist.x64.exe


### How to use it in Python 

```python
import cv2
import numpy as np
from locate_pixelcolor_cpp_parallelfor import search_colors
# 4525 x 6623 x 3 picture https://www.pexels.com/pt-br/foto/foto-da-raposa-sentada-no-chao-2295744/
picx = r"C:\Users\hansc\Downloads\pexels-alex-andrews-2295744.jpg"
pic = cv2.imread(picx)
colors0 = np.array([[255, 255, 255]],dtype=np.uint8)
resus0 = search_colors(pic=pic, colors=colors0, cpus=5)
colors1=np.array([(66,  71,  69),(62,  67,  65),(144, 155, 153),(52,  57,  55),(127, 138, 136),(53,  58,  56),(51,  56,  54),(32,  27,  18),(24,  17,   8),],dtype=np.uint8)
resus1 =  search_colors(pic=pic, colors=colors1, cpus=4)
print(resus1)
####################################################################
# Pretty good, but this one is better: https://github.com/hansalemaos/locate_pixelcolor_cpppragma
%timeit resus0 =  search_colors(pic=pic, colors=colors0, cpus=5)
69.4 ms Â± 302 Âµs per loop (mean Â± std. dev. of 7 runs, 10 loops each)

b,g,r = pic[...,0],pic[...,1],pic[...,2]
%timeit np.where(((b==255)&(g==255)&(r==255)))
150 ms Â± 209 Âµs per loop (mean Â± std. dev. of 7 runs, 10 loops each)
####################################################################
%timeit resus1 =  search_colors(pic=pic, colors=colors1, cpus=5)
151 ms Â± 10.2 ms per loop (mean Â± std. dev. of 7 runs, 10 loops each)

%timeit np.where(((b==66)&(g==71)&(r==69))|((b==62)&(g==67)&(r==65))|((b==144)&(g==155)&(r==153))|((b==52)&(g==57)&(r==55))|((b==127)&(g==138)&(r==136))|((b==53)&(g==58)&(r==56))|((b==51)&(g==56)&(r==54))|((b==32)&(g==27)&(r==18))|((b==24)&(g==17)&(r==8)))
1 s Â± 16.1 ms per loop (mean Â± std. dev. of 7 runs, 1 loop each)
####################################################################
```


### The C++ Code 

```cpp
#include <atomic>
#include <ppl.h>

std::atomic<int> value(0);

int create_id()
{
    return std::atomic_fetch_add(&value, 1);
}

extern "C" __declspec(dllexport) void colorsearch(char *pic, char *colors, int width, int totallengthpic, int totallengthcolor, int *outputx, int *outputy, int *lastresult)
{
    value = 0;

    concurrency::parallel_for(0, totallengthcolor / 3 + 1, [&](int i)
                              {
        int r = i * 3;
        int g = i * 3 + 1;
        int b = i * 3 + 2;
        for (int j = 0; j <= totallengthpic; j += 3)
        {
            if ((colors[r] == pic[j]) && (colors[g] == pic[j + 1]) && (colors[b] == pic[j + 2]))
            {
                int dividend = j / 3;
                int quotient = dividend / width;
                int remainder = dividend % width;
                int upcounter = create_id();
                outputx[upcounter] = quotient;
                outputy[upcounter] = remainder;
                lastresult[0] = upcounter;
            }
        } });
}
// cl.exe /std:c++20 /fp:fast /EHsc /Oi /Ot /Oy /Ob3 /GF /Gy /MD /openmp /LD cloop.cpp /Fe:cloop.dll
```
