Implementasi DeepFace dan OpenCV untuk Prediksi Umur dan Jenis Kelamin Berdasarkan Citra Wajah: Penelitian - M. Iqbal GF; Amar Khadafi; Aryo Satrio W; Dzattho Key Fani; Imam Budiawan; Desmulyati Desmulyati (Jurnal Pengabdian Masyarakat dan Riset Pendidikan, 2026)
The development of Artificial Intelligence technology in the field of facial image processing has encouraged the emergence of various methods for automatically analyzing human attributes. This study implements the DeepFace and OpenCV libraries to detect faces and predict age and gender based on human facial images. DeepFace provides integration with various pre-trained models such as VGG-Face, OpenFace, and DeepID so that the analysis process can be carried out without retraining. This study uses several stages starting from image upload, face detection, facial attribute analysis, and visualization of the prediction results. From the tests conducted, the system successfully identified faces stably and provided relatively accurate age and gender estimates, especially in images with sufficient lighting and frontal facial poses. The results of this study indicate that DeepFace can be used as a practical solution in the development of facial image-based biometric systems.