How to Scrape High‑Resolution Images from ColorHub with Python

Introduction

Many people need high‑quality, royalty‑free images for PPTs but often wonder where to find them. This article introduces ColorHub, a free image site for personal and commercial use, and shows how to download its pictures to a local library for offline use.

Scraping Approach

The image‑scraping process involves three layers of web pages:

Top‑level page : the search result list obtained from the site’s homepage search bar.

Second‑level page : the detail page of each image clicked from the list.

Target page : the actual high‑resolution image URL embedded in the detail page’s source code.

The following diagrams illustrate the three layers:

# import third‑party packages
import requests
from bs4 import BeautifulSoup
import random
import time
from fake_useragent import UserAgent

# loop through pages 1‑10
for page in range(1, 11):
    fst_url = f'https://colorhub.me/search?tag=data&page={page}'
    UA = UserAgent()
    fst_response = requests.get(fst_url, headers={'User-Agent': UA.random})
    fst_soup = BeautifulSoup(fst_response.text)
    sec_urls = [i.find('a')['href'] for i in fst_soup.findAll(name='div', attrs={'class':'card'})]
    pic_names = [i.find('a')['title'] for i in fst_soup.findAll(name='div', attrs={'class':'card'})]
    for sec_url, pic_name in zip(sec_urls, pic_names):
        UA = UserAgent()
        ua = UA.random
        sec_response = requests.get(sec_url, headers={'User-Agent': ua})
        sec_soup = BeautifulSoup(sec_response.text)
        pic_url = 'https:' + sec_soup.find('img', {'class':'card-img-top'})['src']
        pic_response = requests.get(pic_url, headers={'User-Agent': ua})
        with open(pic_name + '.jpg', mode='wb') as fn:
            fn.write(pic_response.content)
        seconds = random.uniform(1, 3)
        time.sleep(seconds)

Conclusion

Executing the script downloads 325 high‑resolution images from the first ten pages of ColorHub, which can be used offline for PPT creation; you can replace the top‑level URL to scrape other categories such as business, architecture, or plants.