Good question. I thought of an algorithm to find the hex word colors that most closely match the color they represent...

Basically: get the color of the _word_ by doing an image search and extracting the dominant color from the first image result. Then compare that color to the hex color (in CIELAB color space) to get the color difference. Track the hex words with lowest difference.

Here's a rough impl in Python:

import sys
import os
import heapq

import requests
from google.cloud import vision

from colormath.color_objects import sRGBColor, LabColor
from colormath.color_conversions import convert_color
from colormath.color_diff import delta_e_cie2000

from bs4 import BeautifulSoup

def download_image_for_query(query):
search_key = os.getenv("GOOGLE_CUSTOM_SEARCH_ENGINE_KEY")
search_engine_id = os.getenv("GOOGLE_CUSTOM_SEARCH_ENGINE_ID")
resp = requests.get(
f"https://www.googleapis.com/customsearch/v1?key={search_key}&cx={search_engine_id}&q={query}&searchType=image"
)
img_url = resp.json()["items"][0]["link"]
img_content = requests.get(img_url).content
return img_content

def dominant_rgb_colors(image_content, num_colors=1):
vision_client = vision.ImageAnnotatorClient()
image = vision.Image(content=image_content)
response = vision_client.annotate_image({"image": image})
return [
(int(c.color.red), int(c.color.green), int(c.color.blue))
for c in response.image_properties_annotation.dominant_colors.colors
][:num_colors]

# class to store hex word and calculate the difference from "true" image, based on image search
class HeapibleHexWord:
def generate_rgb_version(self):
return tuple(int(self.hex_version.lstrip("#")[i:i+2], 16) for i in (0, 2, 4))

def __init__(self, hex_version, english_version):
self.hex_version = hex_version
self.english_version = english_version
self.rgb_version = self.generate_rgb_version()
self.delta_from_true = float("inf")

def calculate_delta_from_true(self):
true_rgb = sRGBColor(*self.rgb_version)
query = self.english_version
img_content = download_image_for_query(query)
test_rgb = sRGBColor(*dominant_rgb_colors(img_content)[0])

# via http://hanzratech.in/2015/01/16/color-difference-between-2-colors-using-python.html
delta = delta_e_cie2000(
convert_color(true_rgb, LabColor),
convert_color(test_rgb, LabColor)
)
self.delta_from_true = delta

def __lt__(self, other):
return self.delta_from_true < other.delta_from_true

# scrape words from hexwords site
hexwords_url = 'https://hexwords.netlify.app/'

hexwords_page = requests.get(hexwords_url)
soup = BeautifulSoup(hexwords_page.text, 'html.parser')

buttons = soup.find_all('button', class_='svelte-1m9ptdb')

hex_words = []
for button in buttons:
if button.text == '':
continue
hex_version, _, english_version = button.text.split("\n")
hex_words.append((hex_version, english_version.replace("(", "").replace(")", "")))

# iterate over the hex words, calculating the color diff between the word's hex
# color and the "true" color based on image search

hex_words_heap = []
heapq.heapify(hex_words_heap)

NUM_WORDS = 10 # looks like throttled at some point

for i, hex_word in enumerate(hex_words[:NUM_WORDS]):
print(f"working on {i}: {hex_word}")
heapible_hex_word = HeapibleHexWord(*hex_word)
heapible_hex_word.calculate_delta_from_true()
heapq.heappush(hex_words_heap, heapible_hex_word)

# popping from the min heap yields hexwords with smallers difference from true color
heapq.heappop(hex_words_heap).english_version