For my academic project I need a small, self-contained Python program that can tell, from a single JPEG image, whether a chair is empty or occupied. The workflow I have in mind is simple: • I place a JPEG file which have multiple chairs in it (or pass its path as an argument). • Your script runs and prints, logs, or returns how many chairs are occupied. The input will always be a static image, not a live feed or video stream. Beyond that, I’m flexible: you can rely on classical OpenCV techniques, a lightweight CNN in TensorFlow or PyTorch, or any hybrid approach you feel offers the best accuracy–as long as the code is clean, well commented, and easy for me to explain in class. Please include in the hand-over: 1. Source code (.py) with in-line comments. 2. A short README describing environment setup, how to run the script, and how the detection logic works. 3. Optional sample images or links to any open dataset you used for testing, so I can reproduce your results. Accuracy matters, but clarity and reproducibility matter even more for this assignment. If you think a pre-trained model or transfer learning will speed things up, feel free to recommend it as part of your proposal.