SeeMyRace is a full-stack, Dockerized Flask platform for race photography—Google Drive ingest, bib and selfie search, and Google OAuth. I led bib-number detection research (including SWT), shipped much of the main site UI, flagging and moderation flows, and backend connectors into the ML inference pipeline. For OCR, I evaluated Tesseract and PaddleOCR; PaddleOCR looked strongest for our task, but at the time its docs skewed Chinese-heavy and were hard to operationalize for a lean MVP.
I architected DeepFace-based semantic facial recognition targeting sub-50ms inference and an asynchronous ingestion pipeline that kept heavy model work off the request path, with UI staying responsive (under 100ms) during bulk uploads. Separately, the product’s face matching also relies on PostgreSQL with pgvector (cosine similarity over embeddings)—that vector search path wasn’t my direct implementation focus. The repo has since gained contributors and more CV plumbing (e.g. YOLOv8, InsightFace), while goals stay aligned.