# Provides functions (Cython - C) for color analysis in images, including finding unique colors, counting occurrences, and comparing images
## pip install cythonimagetools
### Tested against Windows / Python 3.11 / Anaconda
## Cython (and a C/C++ compiler) must be installed
```python
import numpy as np
from cythonimagetools import get_unique_colors, count_colors, get_most_frequent_colors, get_rgb_coords, \
get_rgb_coords_parallel, compare_rgb_values_of_2_pics, find_color_ranges
# Generate a random image
np.random.seed(0)
x = np.random.randint(0, 9, (1000, 1000, 3))
# Get unique colors in the image
uniquecolors = get_unique_colors(x)
print(uniquecolors)
# Count the occurrence of each color in the image
allcolors = count_colors(x)
print(allcolors)
# Get the most frequent colors in the image
most_freq_colors = get_most_frequent_colors(x)
print(most_freq_colors)
# Get RGB coordinates of each pixel in the image
rgb_coords = get_rgb_coords(x)
print(rgb_coords)
# Get RGB coordinates in parallel
rgb_coords_parallel = get_rgb_coords_parallel(x)
print(rgb_coords_parallel)
# Compare RGB values of two images within a specified tolerance
pic1 = np.random.randint(0, 255, (1000, 1000, 3), dtype=np.uint8)
pic2 = np.random.randint(0, 200, (1000, 1000, 3), dtype=np.uint8)
ru = compare_rgb_values_of_2_pics(pic1, pic2, rmax=10, gmax=10, bmax=10)
print(ru)
# Find color ranges in an image based on given colors and tolerance
colors = np.array([[2, 7, 4], [4, 7, 2]], dtype=np.uint8)
foundcolors = find_color_ranges(x, colors, rmax=1, gmax=1, bmax=2)
print(foundcolors)
print(uniquecolors)
print('--------------------')
print(allcolors)
print('--------------------')
print(most_freq_colors)
print('--------------------')
print(rgb_coords)
print('--------------------')
print(rgb_coords_parallel)
print('--------------------')
print(ru)
print('--------------------')
print(colors)
print('--------------------')
print(foundcolors)
print('--------------------')
# [[3 0 5]
# [3 7 3]
# [4 2 5]
# ...
# [2 0 7]
# [3 8 5]
# [2 4 1]]
# --------------------
# [[ 3 0 5 1402]
# [ 3 7 3 1380]
# [ 4 2 5 1369]
# ...
# [ 2 0 7 1413]
# [ 3 8 5 1343]
# [ 2 4 1 1405]]
# --------------------
# [[ 2 7 4 1473]]
# --------------------
# [[ 3 0 5 0 0]
# [ 3 7 3 0 1]
# [ 4 2 5 0 2]
# ...
# [ 6 1 1 999 997]
# [ 0 6 4 999 998]
# [ 8 0 6 999 999]]
# --------------------
# [[ 3 0 5 0 0]
# [ 3 7 3 0 1]
# [ 4 2 5 0 2]
# ...
# [ 6 1 1 999 997]
# [ 0 6 4 999 998]
# [ 8 0 6 999 999]]
# --------------------
# [[143 76 62 ... 5 920 0]
# [153 80 38 ... 9 190 3]
# [ 42 198 93 ... 8 332 3]
# ...
# [ 71 12 64 ... 5 0 995]
# [174 85 160 ... 7 107 996]
# [193 37 160 ... 0 817 997]]
# --------------------
# [[2 7 4]
# [4 7 2]]
# --------------------
# [[ 4 7 2 ... 1 0 1]
# [ 4 7 2 ... 2 0 22]
# [ 4 7 2 ... 2 0 24]
# ...
# [ 4 7 2 ... 2 999 956]
# [ 4 7 2 ... 2 999 970]
# [ 2 7 4 ... 0 999 987]]
# --------------------
```
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"description": "\r\n# Provides functions (Cython - C) for color analysis in images, including finding unique colors, counting occurrences, and comparing images\r\n\r\n## pip install cythonimagetools\r\n\r\n### Tested against Windows / Python 3.11 / Anaconda\r\n\r\n## Cython (and a C/C++ compiler) must be installed\r\n\r\n\r\n```python\r\nimport numpy as np\r\nfrom cythonimagetools import get_unique_colors, count_colors, get_most_frequent_colors, get_rgb_coords, \\\r\n get_rgb_coords_parallel, compare_rgb_values_of_2_pics, find_color_ranges\r\n\r\n# Generate a random image\r\nnp.random.seed(0)\r\nx = np.random.randint(0, 9, (1000, 1000, 3))\r\n\r\n# Get unique colors in the image\r\nuniquecolors = get_unique_colors(x)\r\nprint(uniquecolors)\r\n\r\n# Count the occurrence of each color in the image\r\nallcolors = count_colors(x)\r\nprint(allcolors)\r\n\r\n# Get the most frequent colors in the image\r\nmost_freq_colors = get_most_frequent_colors(x)\r\nprint(most_freq_colors)\r\n\r\n# Get RGB coordinates of each pixel in the image\r\nrgb_coords = get_rgb_coords(x)\r\nprint(rgb_coords)\r\n\r\n# Get RGB coordinates in parallel\r\nrgb_coords_parallel = get_rgb_coords_parallel(x)\r\nprint(rgb_coords_parallel)\r\n\r\n# Compare RGB values of two images within a specified tolerance\r\npic1 = np.random.randint(0, 255, (1000, 1000, 3), dtype=np.uint8)\r\npic2 = np.random.randint(0, 200, (1000, 1000, 3), dtype=np.uint8)\r\nru = compare_rgb_values_of_2_pics(pic1, pic2, rmax=10, gmax=10, bmax=10)\r\nprint(ru)\r\n\r\n# Find color ranges in an image based on given colors and tolerance\r\ncolors = np.array([[2, 7, 4], [4, 7, 2]], dtype=np.uint8)\r\nfoundcolors = find_color_ranges(x, colors, rmax=1, gmax=1, bmax=2)\r\nprint(foundcolors)\r\n\r\n\r\nprint(uniquecolors)\r\nprint('--------------------')\r\n\r\nprint(allcolors)\r\nprint('--------------------')\r\n\r\nprint(most_freq_colors)\r\nprint('--------------------')\r\n\r\nprint(rgb_coords)\r\nprint('--------------------')\r\n\r\nprint(rgb_coords_parallel)\r\nprint('--------------------')\r\n\r\nprint(ru)\r\nprint('--------------------')\r\n\r\nprint(colors)\r\nprint('--------------------')\r\n\r\nprint(foundcolors)\r\nprint('--------------------')\r\n\r\n\r\n# [[3 0 5]\r\n# [3 7 3]\r\n# [4 2 5]\r\n# ...\r\n# [2 0 7]\r\n# [3 8 5]\r\n# [2 4 1]]\r\n# --------------------\r\n# [[ 3 0 5 1402]\r\n# [ 3 7 3 1380]\r\n# [ 4 2 5 1369]\r\n# ...\r\n# [ 2 0 7 1413]\r\n# [ 3 8 5 1343]\r\n# [ 2 4 1 1405]]\r\n# --------------------\r\n# [[ 2 7 4 1473]]\r\n# --------------------\r\n# [[ 3 0 5 0 0]\r\n# [ 3 7 3 0 1]\r\n# [ 4 2 5 0 2]\r\n# ...\r\n# [ 6 1 1 999 997]\r\n# [ 0 6 4 999 998]\r\n# [ 8 0 6 999 999]]\r\n# --------------------\r\n# [[ 3 0 5 0 0]\r\n# [ 3 7 3 0 1]\r\n# [ 4 2 5 0 2]\r\n# ...\r\n# [ 6 1 1 999 997]\r\n# [ 0 6 4 999 998]\r\n# [ 8 0 6 999 999]]\r\n# --------------------\r\n# [[143 76 62 ... 5 920 0]\r\n# [153 80 38 ... 9 190 3]\r\n# [ 42 198 93 ... 8 332 3]\r\n# ...\r\n# [ 71 12 64 ... 5 0 995]\r\n# [174 85 160 ... 7 107 996]\r\n# [193 37 160 ... 0 817 997]]\r\n# --------------------\r\n# [[2 7 4]\r\n# [4 7 2]]\r\n# --------------------\r\n# [[ 4 7 2 ... 1 0 1]\r\n# [ 4 7 2 ... 2 0 22]\r\n# [ 4 7 2 ... 2 0 24]\r\n# ...\r\n# [ 4 7 2 ... 2 999 956]\r\n# [ 4 7 2 ... 2 999 970]\r\n# [ 2 7 4 ... 0 999 987]]\r\n# --------------------\r\n```\r\n",
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