1 files changed, 49 insertions, 0 deletions
diff --git a/src/color_engine.py b/src/color_engine.py
new file mode 100644
index 0000000..f86b2e7
--- /dev/null
+++ b/src/color_engine.py
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+import cv2 as cv
+from sklearn.cluster import KMeans
+
+def grabColors(img_path: str, num_colors: int) -> list():
+    """
+    Takes in an image, and Number of colors, then returns a list of those colors.
+    The list of colors will contain the most prominent colors present in the image.
+    img_path - the path where your image lives (IE, /home/chandler/Pictures/moss.png)
+    num_colors - the number of colors you need back from the image
+    """
+    img = cv.imread(img_path)
+    img = cv.cvtColor(img, cv.COLOR_BGR2RGB)
+    
+    # scale image down by factor of 10 to decrease computation time
+    dim = (int(len(img[0])/10), int(len(img)/10))
+    img = cv.resize(img, dim, interpolation= cv.INTER_AREA)
+    clt = KMeans(n_clusters=num_colors, n_init='auto')
+    clt.fit(img.reshape(-1, 3))
+    return clt.cluster_centers_
+
+def rgbToHex(input_values: list):
+    """
+    Takes in a list of RBG color values and returns a list of those same colors as hex values
+    """
+    hex_list=[]
+    for color in input_values:
+        red = int(color[0])
+        green = int(color[1])
+        blue = int(color[2])
+        hex_list.append('#{:02x}{:02x}{:02x}'.format(red, green, blue))
+    return hex_list
+
+def hexToRGB(hex_value: str):
+    hex_value = hex_value.lstrip('#')
+    return tuple(int(hex_value[i:i+2], 16) for i in (0, 2, 4))
+
+def compColors(color_list: list):
+    """
+    given a list of colors, generate complimentary colors to contrast the prominent colors.
+    return a list of these colors.
+    """
+    compliments = []
+    for color in color_list:
+        curr_hex = color[1:] # slice off the # from the hex code
+        rgb = (curr_hex[0:2], curr_hex[2:4], curr_hex[4:6])
+        comp = ['%02X' % (255 - int(a, 16)) for a in rgb]
+        compliments.append('#' + ''.join(comp))
+    return compliments
+