Python GenAI Image Recognition Platform

I’m building a production-ready image-recognition web app that works exclusively with photographs. The core tasks are facial recognition and general image classification; object detection could be added later, but it is not part of this first milestone. You’ll take the project end-to-end: model selection or fine-tuning (TensorFlow / PyTorch, OpenCV, or a comparable GenAI framework), a RESTful API layer, and a lightweight front-end where users can upload images and see results. I already have an AWS account plus a small labelled photo set; you’ll help expand the dataset and optimise accuracy. The workflow I’m envisioning: • Users upload a photo → backend securely stores it, runs preprocessing, then either returns a face-match report or a classification label set with confidence scores. • All calls are authenticated with JWT and logged. • Results must come back in under half a second for a 1080p image on a t3.medium instance. Deliverables • Clean, well-commented Python code (preferably FastAPI) packaged in Docker • Front-end (React / Next.js or similar) for upload and result display • Unit & integration tests covering 80 % of the codebase • README and deployment script for AWS (CloudFormation or Terraform) Acceptance criteria 1. ≥ 90 % accuracy on the validation set I’ll provide 2. Latency target met for both facial recognition and classification endpoints 3. CI pipeline passes on every push 4. Complete hand-off with documented setup, model re-training, and rollback steps I’d like to see a working demo within two weeks and a full release six weeks from project start. Let me know which frameworks you prefer and any prior projects that show you can hit these performance numbers.