Official English Documentation for ImageAI!

ImageAI is a python library built to empower developers, reseachers and students to build applications and systems with self-contained Deep Learning and Computer Vision capabilities using simple and few lines of code. This documentation is provided to provide detailed insight into all the classes and functions available in ImageAI, coupled with a number of code examples. ImageAI is a project developed by Moses Olafenwa and John Olafenwa , the DeepQuest AI team.

The Official GitHub Repository of ImageAI is https://github.com/OlafenwaMoses/ImageAI

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Installing ImageAI

ImageAI requires that you have Python 3.5.1 or higher installed as well as some other Python libraries and frameworks. Before you install ImageAI, you must install the following dependencies.

  • Python 3.5.1 or higher, Download Python

  • pip3 , Download PyPi

  • Tensorflow 1.4.0 or higher

    pip3 install --upgrade tensorflow
    
  • Numpy 1.13.1 or higher

    pip3 install numpy
    
  • SciPy .19.1 or higher

    pip3 install scipy
    
  • OpenCV

    pip3 install opencv-python
    
  • Pillow

    pip3 install pillow
    
  • Matplotlib

    pip3 install matplotlib
    
  • h5py

    pip3 install h5py
    
  • Keras

    pip3 install keras
    

Once you have these packages installed on your computer system, you should install ImageAI by running the pip command below. Installing ImageAI

pip3 install https://github.com/OlafenwaMoses/ImageAI/releases/download/2.0.2/imageai-2.0.2-py3-none-any.whl

Once ImageAI is installed, you can start running very few lines of code to perform very powerful computer visions tasks as seen below.

Image Recognition

Find all sample codes and documentation via links in the Content secton below this page.

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  • convertible : 52.459555864334106
  • sports_car : 37.61284649372101
  • pickup : 3.1751200556755066
  • car_wheel : 1.817505806684494
  • minivan : 1.7487050965428352

** Image Object Detection**

Find all sample codes and documentation via links in the Content secton below this page.

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Video Object Detection

Find all sample codes and documentation via links in the Content secton below this page.

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Video Detection Analysis

Find all sample codes and documentation via links in the Content secton below this page.

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Custom Image Recognition Training and Inference

Find all sample codes and documentation via links in the Content secton below this page.

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Follow the links in the Content section below to see all the code samples and full documentation of available classes and functions.

Indices and tables