Chair Occupancy Detection Python Script

@s9iper1

I can deliver a clean, well-documented Python program that detects whether chairs in a single JPEG image are occupied or empty. The solution will use a lightweight, pre-trained object-detection model (e.g., YOLOv8n or MobileNet-SSD) combined with a simple post-processing step to classify each detected chair as occupied based on the presence of a person nearby or seated on it. You’ll receive a fully commented .py script, a concise README explaining setup and logic, and optional sample images or open-dataset references for easy replication. The focus will be clarity, reproducibility, and accuracy suitable for an academic presentation.

@Poenga

Hello, I can build a clear, self-contained Python script that analyzes any JPEG image and returns how many chairs are occupied, using a lightweight, non-heavy model approach suitable for academic presentation. I’ll provide clean, well-commented code, a simple README explaining the detection logic, and sample images or dataset links so you can easily reproduce and explain the results in class.

@singh7509811123

Hello, I can develop a self-contained Python program that analyzes a single JPEG image containing multiple chairs and accurately determines how many of them are occupied. The solution will be simple to run, clearly documented, and suitable for academic presentation. What I will deliver: A clean, well-commented Python script using either classical OpenCV methods or a lightweight deep-learning model (TensorFlow/PyTorch), depending on which provides the best balance of accuracy and simplicity A clear output that prints or logs the total number of occupied chairs A concise README covering environment setup, running instructions, and an easy-to-explain overview of the detection approach Optional sample images or references to open datasets used for testing I focus on creating solutions that are accurate, reproducible, and easy to understand—ideal for academic demonstrations. If a pre-trained model or transfer learning can improve results efficiently, I will integrate it and document it clearly. Ready to start and deliver a reliable, easy-to-present solution.

@abbas021

Hello oboshiney, I’ve gone through your project description carefully, and I’m confident that I can handle this project efficiently. We are an expert team which have many years of experience on JavaScript, Python, Software Architecture, Machine Learning (ML), C++ Programming, Artificial Intelligence, Image Processing, OpenCV, Computer Vision, Deep Learning Please come over chat and discuss your requirement in a detailed way. Thank You

@MoizAhmed003

I can create a self-contained Python script that detects occupied chairs in a static JPEG image using OpenCV and lightweight CNN (TensorFlow/PyTorch). The program will output the number of occupied chairs, be clean, well-commented, and easy to explain. Deliverables include the .py source code, a short README with setup and running instructions, and optional sample images or datasets for reproducibility. Accuracy and clarity will be prioritized. Moiz Ahmed

@rehanr165

hey sir I am a front end web developer I am a dedicated Web Developer specialising in creating highly functional and visually engaging digital solutions. I offer end-to-end development services, focusing on modern, responsive design and robust performance crucial for the British market. My expertise in [Mention 1-2 Key Skills, e.g., React & Node.js] ensures your project will be built for scalability and optimal user experience.

@aayanpandey

I can deliver a fully explained Python script using YOLO to detect chairs and occupancy from any JPEG image. Includes source code, comments, README, and sample tests.