Iris Region Detection Source Code

This source code is designed for iris region detection and can be applied to gaze tracking, eye region detection, and similar computer vision tasks. Additionally, it can be integrated into facial recognition systems to enhance identification accuracy through precise iris localization. The implementation leverages deep learning algorithms, utilizing neural network models for image analysis and processing. The code employs convolutional neural networks (CNNs) to extract hierarchical features from eye images, implementing segmentation techniques to isolate iris boundaries with high precision. Through this codebase, developers can achieve more accurate and efficient iris detection, providing a reliable foundation for subsequent gaze tracking and ocular analysis pipelines. The architecture supports transfer learning approaches, allowing pretrained models to be fine-tuned for specific use cases. Furthermore, the code offers excellent extensibility, featuring modular components that can be modified and optimized according to specific requirements, enabling adaptation to diverse application scenarios through parameter tuning and model retraining. Key functions include image preprocessing routines, neural network inference pipelines, and post-processing modules for refining detection outputs.