davisking
Enhanced AI-Driven Face Recognition: AO3: Enhancement of Performance Rate, Increase of Accuracy, and Enhancement of Robustness of Systems
However, in the recent update of the face recognition script using dlib major changes were made to increase its efficiency and to include AI functionalities. The script of the application was initially designed for face detection, facial landmarks and face descriptors generation. But it has issues concerning execution efficiency, errors dealing with, and enhanced flexibility.
In order to solve those, the given script was changed with several enhancements: Firstly, the dynamic error handling was added to enhance the information provided to the end-user and to avoid program termination in the cases when an incorrect input or a non-existing file is used. This makes it more reliable and easier to use to the various clientele. Also additional conditions were put into the loops and where possible restructuring of loops was done to improve efficiency of the code.
AI-related features were also incorporated to improve on the script’s functionality. The face detection and recognition were enhanced with optimization techniques based on artificial intelligence: face descriptor comparison adopted a variable threshold to respond to optimum detection for similar faces. There are new sliders in the script for the automatic alignment of images with faces using AI which helps to improve the orientation of face images before applying filters, which results in higher quality of the picture.
In addition, the script’s execution time was reduced to include batch processing with the aid of AI parallelism to enable the processing of multiple images at once without delay. This is especially important if one is dealing with big data as the results in this case are massive. The new features also include an AI module that offers an automatic facial landmark enhancement in order to improve the precision of the landmarks detected which is vital for an accurate face recognition.
As a whole, these changes have made the script more versatile and capable when compared to the previous implementation while providing corresponding practical features that can be used in face recognition tasks.
Thanks for the PR. End user applications should go in a separate repository though. You should make one in your account and post it there :)
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