It works by scanning through the pictures in your Windows download folder, documents folder, desktop folder, videos folder, pictures folder and it's subfolders. It obtains the pictures and run a self-contained Intelligence Module prediction on each picture and store the pictures in their respective categories. The Intelligence Module is made possible by the ImageAI library , that enables applications and systems built with Python to have self-contained image prediction capabilities.

You can download the IntelliP Windows installer via this link.

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IntelliP was built using Python 3.5, Kivy (Python UI framework) and ImageAI. The ResNet model is the computer vision model used to power the image prediction.
The entire source code and resources used in building the IntelliP application is included in this repository. The source code have the following dependencies:
- Python 3.5
- Tensorflow 1.4.0
- Numpy 1.14.2
- SciPy 1.0.0
- ImageAI 1.0.1
- Kivy 1.10.0
- Kivy Glew 0.1.9
- Kivy SDL2 0.1.17

In addition to the files contained in this repository, follow this link to download the ResNet model used in the Intelligence Module.

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This application was built to demonstrate the potentials contained in the ImageAI python library for application and systems developements. You can reach to us via our contacts below:

Moses Olafenwa
Website: https://moses.specpal.science
Twitter: @OlafenwaMoses
Medium : @guymodscientist
Facebook : moses.olafenwa


John Olafenwa
Website: https://john.specpal.science
Twitter: @johnolafenwa
Medium : @johnolafenwa
Facebook : olafenwajohn