I’m looking for a Python-driven computer-vision solution that can scan images of wooden surfaces and reliably flag three defect types: • Cracks • Discoloration • Scratches You may choose the techniques—traditional OpenCV pipelines, deep-learning models such as CNNs, or a hybrid approach—but the final system must run entirely in Python and process images or short video clips without manual intervention. Here is what I expect at hand-off: • Clean, well-commented source code with clear instructions for installation and use. • A trained model (or parameter set) and any preprocessing scripts. • A short report outlining the detection logic, performance metrics on your test set, and guidance on how I can retrain or extend the model for new wood species or lighting conditions. Please attach a detailed project proposal that outlines your planned methodology, timeline, and any data requirements you have. Only proposals that explain how you will achieve reliable detection of cracks, discoloration, and scratches on wood surfaces will be considered.