Face Recognition and Face Detection series in Python
- Detecting Faces with 20 lines in Python
- Face Recognition with 20 lines in Python
- Detecting Facial Features with 20 lines in Python
- Facial Features and Face Recognition with 20 lines in Python
- Performance improvements with code
- Resize the camera input with OpenCV
- Working with Haar Cascades and OpenCV
- Detect and blur faces 😁 using haar cascades
- Detect and blur faces 😁 using DNN
I’ve write a lot about how to use AI models in C# to perform tasks like Face recognition, speech analysis, and more. During the Chicago CodeCamp, someone ask me about how to perform Face Recognition in Python. I didn’t have any working sample to showcase this, and I failed in try to write a 2 min app. So I added this into my ToDo list.
For this demo I’ll use Anaconda as the base Python distribution and Visual Studio Code as the code editor. There are several packages to perform face detection in Python. I’ll use a mix between OpenCV and Adam Geitgey Face Recognition package to use the camera and detect and recognize faces.
I’ll start by installing some packages to use in python app: dlib, openCV and face_recognition
"C:/Program Files (x86)/Microsoft Visual Studio/Shared/Anaconda3_86/python.exe" -m pip install dlib --user "C:/Program Files (x86)/Microsoft Visual Studio/Shared/Anaconda3_86/python.exe" -m pip install face_recognition --user "C:/Program Files (x86)/Microsoft Visual Studio/Shared/Anaconda3_86/python.exe" -m pip install opencv-python --user
And, the first step will be to detect faces and draw frames around them. All of this in 20 lines of code
When we run the app, we will see the camera feed and frames around the detected faces. In my next post I’ll add some extra code to perform face recognition.
Greetings @ Toronto