# Detects colors in images up to 8 times as fast as NumPy
### pip install locate-pixelcolor-cupy
If you haven't installed cupy yet, I recommend you installing it using conda:
conda install -c conda-forge cupy
#### Tested against Windows 10 / Python 3.10 / Anaconda
### Usage
```python
import numpy as np
import cv2
from locate_pixelcolor_cupy 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)
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)
####################################################################
%timeit resus0 = search_colors(pic=pic, colors=colors0)
78.2 ms ± 1.29 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
b,g,r = pic[...,0],pic[...,1],pic[...,2]
%timeit np.where(((b==255)&(g==255)&(r==255)))
150 ms ± 209 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)
####################################################################
%timeit resus1 = search_colors(pic=pic, colors=colors1)
139 ms ± 9.78 ms per loop (mean ± std. dev. of 7 runs, 1 loop 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 ± 16.1 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
####################################################################
```
Raw data
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"description": "# Detects colors in images up to 8 times as fast as NumPy \r\n\r\n### pip install locate-pixelcolor-cupy\r\nIf you haven't installed cupy yet, I recommend you installing it using conda:\r\nconda install -c conda-forge cupy\r\n\r\n#### Tested against Windows 10 / Python 3.10 / Anaconda\r\n\r\n\r\n\r\n### Usage\r\n\r\n```python\r\n\r\nimport numpy as np\r\nimport cv2\r\nfrom locate_pixelcolor_cupy import search_colors\r\n# 4525 x 6623 x 3 picture https://www.pexels.com/pt-br/foto/foto-da-raposa-sentada-no-chao-2295744/\r\npicx = r\"C:\\Users\\hansc\\Downloads\\pexels-alex-andrews-2295744.jpg\"\r\npic = cv2.imread(picx)\r\ncolors0 = np.array([[255, 255, 255]], dtype=np.uint8)\r\nresus0 = search_colors(pic=pic, colors=colors0)\r\ncolors1 = np.array(\r\n [\r\n (66, 71, 69),\r\n (62, 67, 65),\r\n (144, 155, 153),\r\n (52, 57, 55),\r\n (127, 138, 136),\r\n (53, 58, 56),\r\n (51, 56, 54),\r\n (32, 27, 18),\r\n (24, 17, 8),\r\n ],\r\n dtype=np.uint8,\r\n)\r\nresus1 = search_colors(pic=pic, colors=colors1)\r\n####################################################################\r\n%timeit resus0 = search_colors(pic=pic, colors=colors0)\r\n78.2 ms \u00c2\u00b1 1.29 ms per loop (mean \u00c2\u00b1 std. dev. of 7 runs, 1 loop each)\r\n\r\nb,g,r = pic[...,0],pic[...,1],pic[...,2]\r\n%timeit np.where(((b==255)&(g==255)&(r==255)))\r\n150 ms \u00c2\u00b1 209 \u00c2\u00b5s per loop (mean \u00c2\u00b1 std. dev. of 7 runs, 10 loops each)\r\n####################################################################\r\n%timeit resus1 = search_colors(pic=pic, colors=colors1)\r\n139 ms \u00c2\u00b1 9.78 ms per loop (mean \u00c2\u00b1 std. dev. of 7 runs, 1 loop each)\r\n\r\n%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)))\r\n1 s \u00c2\u00b1 16.1 ms per loop (mean \u00c2\u00b1 std. dev. of 7 runs, 1 loop each)\r\n####################################################################\r\n```\r\n",
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