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Image color extraction from web image search

Project description

version github python35 license format

This module uses imagecolor with PIL(Pillow) to extract colors from web image searches.

Available functions

average_image_url(url, name)

Averages a single image from a url into RGB color values. Returns a dictionary with the following keys: name, red, green, blue

  • url - image url.

  • name - name to return. Generally passed from the function that generates the url.

  • timeout - requests timeout in seconds.

  • max_size - maximum size of image to fetch in MB.

_image_search_average(url_list, max_threads=20)

Averages all urls in a list into a singular RGB average.

  • url_list - path to directory

  • max_threads - max processes to spawn.

  • timeout - requests timeout in seconds. This gets passed to average_image_url

  • max_size - maximum size of image to fetch in MB. This gets passed to average_image_url

google_average(search_term, num_results, api_key, cse_id, max_threads=20)

Does a Google image search and averages all the images into a singular RGB search average. Returns a dictionary with the following keys: name, red, green, blue

  • search_term - Google image search term.

  • num_results - Number of results to include.

  • api_key - Google API key.

  • cse_id - Google CSE ID.

  • max_threads - max processes to spawn. This gets passed to \_image_search_average

  • timeout - requests timeout in seconds. This gets passed to average_image_url

  • max_size - maximum size of image to fetch in MB. This gets passed to average_image_url

Future work

  • add more information to readme

  • build offline tests

Tests

Testing is done with pytest

Currently tests only the google api. Requires the enviroment variables GOOGLE_SEARCH_API and GOOGLE_SEARCH_CSE to be set to a valid google custom search api and id

Run with python3 setup.py test

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