guerinsylvain / computer-vision

Learning how to implement face detection and recognition in video stream

Some useful computer vision resources

Long term objective is to build a tool to detect personalities in videos

References
Setup
   Get the sources
   Install Visual C++ Tools for Cmake
   Install the CUDA Toolkit 10.1
   Install the NVIDIA CUDA Deep Neural Network library (cuDNN v7.6.5 (November 5th, 2019), for CUDA 10.1)
   Install and configure Python

References

Here are some references that helped me to build this experiment:

• Hands-On Computer Vision with TensorFlow 2: Leverage deep learning to create powerful image processing apps with TensorFlow 2.0 and Keras by Benjamin Planche and Eliot Andres
• YoloV3 Implemented in TensorFlow 2.0 by Zihao Zhang
• Face Recognition

Setup

Get the sources

You may

• clone this github repository
• or download a zip containing the latest version or a given release of the code

Install Visual C++ Tools for Cmake

1. Install Visual Studio build tools from here.
2. In Visual Studio 2017 go to the Individual Components tab, Visual C++ Tools for Cmake, and check the checkbox under the "Compilers, build tools and runtimes" section.

Install the CUDA Toolkit 10.1

1. Please install from the following link
   Note that you can uncheck "Install Visual Studio Extensions" in the options.

Install the NVIDIA CUDA Deep Neural Network library (cuDNN v7.6.5 (November 5th, 2019), for CUDA 10.1)

1. Follow the instructions detailed here
   Make sure to install the version v7.6.5 (November 5th, 2019), for CUDA 10.1

Install and configure Python

1. Install Python 3.7 or later.
2. From the root folder of the project, type

   pip install virtualenv
   

3. Then type

   virtualenv --python="C:\Users\[YOUR USER NAME]\AppData\Local\Programs\Python\Python37\python.exe" venv      
   

   This will create a venv subfolder.
   Note that the path to the python.exe (v3.7) may vary on your machine. If python has been installed with visual studio, you may have something similar to this:

   virtualenv --python="C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\python.exe" venv
   

4. From the root folder of the project, activate the virtual environment by typing:

   .\venv\Scripts\activate.bat
   

5. Install packages:

   pip install -r requirements.txt