A PyTorch implementation of the 'FaceNet' paper for training a facial recognition model with Triplet Loss using the glint360k dataset. A pre-trained model using Triplet Loss is available for download.
Keras implementation of the renowned publication "DeepFace: Closing the Gap to Human-Level Performance in Face Verification" by Taigman et al. Pre-trained weights on VGGFace2 dataset.
Glint is a Rust framework designed for creating stateful, graph-based AI systems, enabling efficient multi-step workflows. With features like LLM integration and a graph-based architecture, Glint helps developers build powerful AI solutions with ease. 🐙✨
FINAL YEAR PROJECT ON DEEPFAKE DETECTION WITH CNN (USING PYTORCH)
End-to-end Person Identification System using Deep Learning, FastAPI backend, and Django frontend for real-time image-based identification.
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