Developer Builds AI System That Identifies Dogs by Their Nose-Print

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A developer has created Nose ID, a biometric identification system that recognizes individual dogs by scanning their nose-prints instead of relying on collars or tags. The system uses a pretrained MobileNetV2 neural network to extract facial embeddings and cosine similarity matching to identify each dog. Google Gemini generates a fun personality bio for each identified dog, while ElevenLabs converts the result into a spoken voice confirmation. The project was built using a React-Vite frontend and a FastAPI Python backend, with PyTorch handling the machine learning components. During development, the creator encountered mid-project API changes from both Google and ElevenLabs, requiring workarounds to keep the system functional.

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