# RGB search with numba.cuda - 10 x faster than numpy
### pip install locate-pixelcolor-numbacuda
```python
from locate_pixelcolor_numbacuda import search_colors
from a_cv_imwrite_imread_plus import open_image_in_cv
import numpy as np
colors=[(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),]
```
#### image'https://www.pexels.com/pt-br/foto/foto-da-raposa-sentada-no-chao-2295744/'
```python
picnp = open_image_in_cv('pexels-alex-andrews-2295744.jpg',channels_in_output=3)
coords=search_colors(pic=picnp,colors=colors,threadsperblock=(18, 18,3),dtypetouse = np.int32)
print(coords)
%timeit search_colors(pic=picnp,colors=colors,threadsperblock=(18, 18,3),dtypetouse = np.int32)
# [[[ 19 14]
# [ 19 14]
# [ 11 17]
# ...
# [6613 4524]
# [6614 4524]
# [6615 4524]]]
# 135 ms ± 3.5 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)
# More benchmarks: https://github.com/hansalemaos/locate_pixelcolor_cpp
```
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