Image color extraction from web image search
Project description
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
Project details
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