# RGB search with numba - 2-3 x faster than numpy
### pip install locate-pixelcolor-numba
### Important!
This is a compiled .pyd file (Numba AOT), if you can't import it, run the following code to generate a new pyd file, and replace it with the old .pyd file.
```python
from numba_aot_compiler import compnumba #pip install numba-aot-compiler
import numpy as np
from numba import uint8, uint16
def search_colors(r, g, b, rgbs, divider):
res = np.zeros(b.shape, dtype=np.uint16)
res2 = np.zeros(b.shape, dtype=np.uint16)
zaehler = 0
for rgb in rgbs:
rr, gg, bb = rgb
for i in range(r.shape[0]):
if r[i] == rr:
if g[i] == gg:
if b[i] == bb:
dvquot, dvrem = divmod(i, divider)
res[zaehler] = dvquot
res2[zaehler] = dvrem
zaehler = zaehler + 1
results = np.dstack((res[:zaehler], res2[:zaehler]))
return results
compi2 = compnumba(
fu=search_colors,
funcname="search_colors",
file="searchcolorsnumba",
folder="locate_pixelcolor_numba",
signature=(uint8[:], uint8[:], uint8[:], uint8[:, :], uint16),
parallel=True,
fastmath=True,
nogil=True,
)
```
### How to use it
```python
from locate_pixelcolor_numba import search_colors
import cv2
import time
import numpy as np
pic = cv2.imread(r"pexels-alex-andrews-2295744.jpg") # https://www.pexels.com/pt-br/foto/foto-da-raposa-sentada-no-chao-2295744/
colors = 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)
search_colors(pic,colors)
Out[2]:
array([[[ 0, 4522],
[ 3, 4522],
[ 3, 4523],
...,
[6622, 4522],
[6622, 4523],
[6622, 4524]]], dtype=uint16)
%timeit search_colors(pic,colors)
413 ms ± 1.22 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
# More benchmarks: https://github.com/hansalemaos/locate_pixelcolor_cpp
```
Raw data
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