<jupyter_start><jupyter_text>Google Image Scrapper for Juypter Notebook<jupyter_code>from GoogleImageScrapper import GoogleImageScraper
import os
import time

sleep_between_interactions = 1
webdriver_path = os.getcwd()+".\\webdriver\\chromedriver.exe"
image_path = os.getcwd()+".\\animal"
#image_path = os.getcwd()+"\\photos"
#add new search key into array ["cat","t-shirt","apple","orange","pear","fish"]
#search_keys= ["woodpecker","owl"]
search_keys= ["만두", "새우튀김", "치즈"]
number_of_images = 120
headless = False
#min_resolution = (width,height)
min_resolution=(0,0)
#max_resolution = (width,height)
max_resolution=(2500,2500)
for search_key in search_keys:
    image_scrapper = GoogleImageScraper(webdriver_path,image_path,search_key,number_of_images,headless,min_resolution,max_resolution)
    image_urls = image_scrapper.find_image_urls()
    image_scrapper.save_images(image_urls)
    time.sleep(sleep_between_interactions)<jupyter_output>GoogleImageScraper Notification: Scraping for image link... Please wait.
0. https://upload.wikimedia.org/wikipedia/commons/0/0c/%EB%A7%8C%EB%91%90.jpg
1. https://recipe1.ezmember.co.kr/cache/recipe/2017/09/30/f4ba75b36b297beceda0a3424feec37c1.jpg
2. https://cdn.imweb.me/thumbnail/20190125/5c49d5de95c61.png
3. https://s3.ap-northeast-2.amazonaws.com/event-localnaeil/FileData/Article/202004/56c1b8c3-43e6-466b-8d66-6e56a770206c.jpg
4. https://pds.joins.com//news/component/htmlphoto_mmdata/201802/07/12621b47-8458-4025-9c77-e6930ac4c3ab.jpg
5. https://i.ytimg.com/vi/RSmTGg1yPv4/maxresdefault.jpg
6. https://cdn.imweb.me/thumbnail/20190328/5c9c56391ab8a.jpg
7. https://img.insight.co.kr/static/2019/08/22/700/c5e8tj7z81p4io3s71jm.jpg
8. https://recipe1.ezmember.co.kr/cache/recipe/2015/12/31/6f4172b42356611dccce894a02e10446.jpg
9. https://image.auction.co.kr/itemimage/17/04/c6/1704c64a26.jpg
10. https://shop.hansalim.or.kr/im/is/activeDesigner/080305029_content1.jpg
11. https://homecuisine.co.kr[...]
{'fraction_non_alphanumeric': 0.14974358974358976, 'fraction_numerical': 0.11948717948717949, 'mean_word_length': 6.017985611510792, 'pattern_counts': {'":': 0, '<': 4, '<?xml version=': 0, '>': 4, 'https://': 12, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '116061', 'license': 'MIT', 'n_tokens_mistral': 938, 'n_tokens_neox': 821, 'n_words': 85, 'path': 'juypter_main.ipynb', 'repo_name': 'qwerlarlgus/Object_detection', 'size': '1950'}