<jupyter_start><jupyter_text>https://joedockrill.github.io/jmd_imagescraper/<jupyter_code>!pip install jmd_imagescraper<jupyter_output>Collecting jmd_imagescraper
  Downloading jmd_imagescraper-1.0.2-py3-none-any.whl (12 kB)
Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from jmd_imagescraper) (2.23.0)
Requirement already satisfied: fastprogress in /usr/local/lib/python3.7/dist-packages (from jmd_imagescraper) (1.0.0)
Requirement already satisfied: Pillow in /usr/local/lib/python3.7/dist-packages (from jmd_imagescraper) (7.1.2)
Requirement already satisfied: ipywidgets in /usr/local/lib/python3.7/dist-packages (from jmd_imagescraper) (7.6.5)
Requirement already satisfied: bs4 in /usr/local/lib/python3.7/dist-packages (from jmd_imagescraper) (0.0.1)
Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from jmd_imagescraper) (1.3.5)
Requirement already satisfied: pathlib in /usr/local/lib/python3.7/dist-packages (from jmd_imagescraper) (1.0.1)
Requirement already satisfied: beautifulsoup4 in /usr/local/lib/python3.7/dist-packages (from bs4->jmd_imagescraper[...]<jupyter_text>Importing the main classes<jupyter_code>from jmd_imagescraper.core import * # dont't worry, it's designed to work with import *
from pathlib import Path<jupyter_output><empty_output><jupyter_text>Set root = /system path + /current working directory + /images<jupyter_code>root = Path().cwd()/"images"<jupyter_output><empty_output><jupyter_text>Scrape images from duckduckgo*   Cats = destination directory*   cute kittens = keywords to search<jupyter_code>duckduckgo_search(root, "Cats", "cute kittens", max_results=20)<jupyter_output>Duckduckgo search: cute kittens
Downloading results into /content/images/Cats<jupyter_text>Clean images<jupyter_code>from jmd_imagescraper.imagecleaner import *
display_image_cleaner(root)<jupyter_output><empty_output><jupyter_text>Compress all images to single zip file<jupyter_code>!zip -r /content/ImagesfromColab.zip /content/images<jupyter_output>adding: content/images/ (stored 0%)
  adding: content/images/Cats/ (stored 0%)
  adding: content/images/Cats/018_e5bcee85.jpg (deflated 1%)
  adding: content/images/Cats/019_79f13b24.jpg (deflated 0%)
  adding: content/images/Cats/002_bd133f41.jpg (deflated 1%)
  adding: content/images/Cats/010_4eef4d9f.jpg (deflated 1%)
  adding: content/images/Cats/015_fddec604.jpg (deflated 1%)
  adding: content/images/Cats/004_c28f0096.jpg (deflated 1%)
  adding: content/images/Cats/012_2c9078f1.jpg (deflated 1%)
  adding: content/images/Cats/016_b5585aca.jpg (deflated 3%)
  adding: content/images/Cats/005_0011504d.jpg (deflated 1%)
  adding: content/images/Cats/017_e2dbf125.jpg (deflated 0%)
  adding: content/images/Cats/007_22bfeb62.jpg (deflated 1%)
  adding: content/images/Cats/011_d5ed819a.jpg (deflated 1%)
  adding: content/images/Cats/013_2ba2818f.jpg (deflated 1%)
  adding: content/images/Cats/003_6a351f62.jpg (deflated 1%)
  adding: content/images/Cats/020_9c6ccd58.jpg (deflated 1%)
  ad[...]<jupyter_text>You can download zip file to your computer Homeworkthink about your own image classification project<jupyter_code><jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11617738913179262, 'fraction_numerical': 0.056527170518425984, 'mean_word_length': 6.246606334841629, 'pattern_counts': {'":': 0, '<': 26, '<?xml version=': 0, '>': 27, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 3, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '7', 'dir': 'jupyter-structured-clean-dedup', 'id': '291657', 'license': 'MIT', 'n_tokens_mistral': 1300, 'n_tokens_neox': 1192, 'n_words': 221, 'path': 'Adding EP.02 - Create your own dataset in 10 minutes! (Secret).ipynb', 'repo_name': 'GemmyTheGeek/FastaiForKids', 'size': '3202'}