Face_recognition_realtime

people detection and face recognition

Steps For Installation

1. Install Anaconda.

2. Open Anaconda Prompt.

3. Create conda virtual environment

   • Conda create -n venv anaconda python==3.10.0
   • conda activate venv

4. You need to install Microsoft build tools from this link (or latest) https://aka.ms/vs/17/release/vs_BuildTools.exe Or from official website of Visual Studio Installer. (If you have already installed Visual Studio Installer goto “Modify” option and continue the remaining steps)

5. Select “Desktop Development with C++”.

6. And Install

7. Install the required libraries in the virtual environment

   • numpy - 1.25.2

   • pandas - 2.0.3

   • matplotlib - 3.7.2

   • scipy - 1.11.1

   • jupyter- 1.0.0

   • opencv-python - 4.8.0

   • By running the command “pip3 install ”

8. Install InsightFace

   • pip3 install insightface==0.7.3

9. Install opencv-python

10. Install onnxruntime (InsightFace Dependency)

    • pip3 install onnxruntime==1.15.1

11. Install Cuda 12.2

    • Sudo apt install nvidia-cuda-toolkit

12. Check InsightFace Installation.

    • Open Python in the Terminal
    • Run “import insightface”, properly installed, if it runs successfully.

13. Setting Up Redis Database.

    • Pip3 install redis-server OR Download the “redis-x64-3.0.504.zip/” from “https://github.com/MicrosoftArchive/redis/releases”
    • Extract the file and click on “redis-server” in the new directory.
    • Click on the file “redis-CLI” and type “ping”, it will result in “PONG”.
    • create a hkey in redis

Note:- After creating a virtual environment using Anaconda, for activating a virtual environment you to open Anaconda Prompt and activate it by - conda activate <virtual_environment>

Steps For Running

1. Activate the Virtual Environment and go to the project location.
2. for training create a folder a upload the videos of faces of individual with the name of the video as "name#emaild" after that run "video_training.py" file
3. After training is ompleted Run "object_detection.py"