https://github.com/mikemaccana/pyfilter

Python client for pifilter adult image detection service (www.pifilter.com). Useful for helping automate moderation on public forums.
https://github.com/mikemaccana/pyfilter

Last synced: 5 days ago
JSON representation

Python client for pifilter adult image detection service (www.pifilter.com). Useful for helping automate moderation on public forums.

• Host: GitHub
• URL: https://github.com/mikemaccana/pyfilter
• Owner: mikemaccana
• Created: 2010-10-20T15:30:21.000Z (about 14 years ago)
• Default Branch: master
• Last Pushed: 2010-10-20T16:19:56.000Z (about 14 years ago)
• Last Synced: 2024-10-12T01:27:40.793Z (about 1 month ago)
• Homepage:
• Size: 93.8 KB
• Stars: 7
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.markdown

Awesome Lists containing this project

README

        
PyFilter

========

## Introduction

This is a Python client for PIFilter, a paid, web based image recognition service.

It provides a simple True/False response to whether an image is adult related. It is useful in:

- User generated content sites 

- Content-filtering proxy scanners

### Filtering images

- Get a [pifilter account and customer ID](http://www.pifilter.com/).

- Then [download pyfilter](http://github.com/mikemaccana/pyfilter/tarball/master).

- Use **pip** or **easy_install** to fetch the **urllib2** and **poster** modules. 

Then run:

	from pyfilter import checkimage

	

	checkimage('some/file.jpg','your_own_customer_id')

The response will be a simple True or False.

By default pyfilter runs in 'aggressive' mode, where 'maybe' responses are counted as True. You may prefer to run:

	checkimage('some/file.jpg','your_own_customer_id',aggressive=False)

which will count 'maybe' responses as False. 

### General thoughts on PIFilter

In my own experience as a customer PIFilter's service is like health product that works best with diet and exercise. It is useful as a basis to put specific posts ahead in a moderation queue, where the suspect posts are checked by a human. But it's not sufficient on its own to replace human moderations completely. 

With my own user generated content tests, accuracy was generally good with a tendency towards False positives rather than False negatives.

Of course, your milage may vary as you'll be working with a different set of input, so best to see for yourself.

### We love forks, changes and pull requests!

- For this project on github

- Send a pull request via github and we'll add your changes!

### License

Licensed under the [MIT license](http://www.opensource.org/licenses/mit-license.php)

Short version: this code is copyrighted to me (Mike MacCana), I give you permission to do what you want with it except remove my name from the credits. See the LICENSE file for specific terms.