So which of these actually spell the color they represent (or something closely related)? From a quick glance, I have no found any. Do color-words like that exist in other languages maybe?
#1C1E57 (ICIEST) is dark blue, which could hold true in certain contexts!
#DEBA65 (DEBAGS) is brown, much like de color of de bags made of de paper.
And on a related and exceptionally juvenile note, it should be very possible - and frankly obligatory, for those in fashion tech companies reading this - to create and sell a #B00B1E colored bra.
The concept of people leaving audio messages _with a reasonable expectation that someone will listen to them_ is (thankfully) dying out, at least among my social circles.
You can leave a message if you want, I'm not going to listen to it. The only entities that make unexpected phone calls are scammers and bots.
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
The issues isn't the color of the asses, but rather that the word spelled is assess. As in, the tax assessor is coming to assess our property now that we put on that addition. I expect our assessment to go up.
Kind of a stretch, but #B05535 (bosses) and #BE57ED (bested) are both sort of purplish colors that looter games like Borderlands sometimes use for "pretty rare, but not unique" items (which would typically be dropped by a boss monsters when you defeat them).
How many colors do you typically identify or would be willing to accept? Somewhere between 10 and 25 would be sufficient… not every word will have a color association, but many will have more than one.
I think you need to be pretty strict to not find a match after 50 words.
Similar things in a number's value v/s its number of characters I think is called True Number, & only 4 is a true number like 4 value & FOUR has exact 4 letters.
#DEBA65 (DEBAGS) is brown, much like de color of de bags made of de paper.
And on a related and exceptionally juvenile note, it should be very possible - and frankly obligatory, for those in fashion tech companies reading this - to create and sell a #B00B1E colored bra.