I already have a working object-detection pipeline written in Python, and I now need that same logic moved into a cleaner, better-structured Python codebase that’s easy to maintain and integrate into a larger application. Think of it as a conversion/refactor: exact same model, exact same results, but with modern syntax, clear separation of concerns, and thorough inline comments. You’ll start from my original scripts and checkpoints, preserve every bit of accuracy, and hand back a fully functioning module (including a simple demo script) that can be installed with pip-installable requirements. Feel free to streamline library calls—TensorFlow, PyTorch, OpenCV, or whatever is currently in place—so long as the final inference output matches the reference I provide. Deliverables • Refactored Python package replicating the current predictions on a supplied test set • README covering setup, dependencies, and usage • Quick comparison report showing identical mAP or better against the original run I’ll sign off once the side-by-side results confirm parity.