Retail People Tracking & Analytics

@nrajuu07

I'm a computer vision engineer experienced in multi-camera tracking and retail analytics. I'll build a complete Python pipeline using YOLOv8, ByteTracker, and a Re-ID module — detecting and tracking shoppers only, preserving cross-camera identity to eliminate double-counting, filtering staff via appearance-based classification, and producing foot-traffic counts, crowd-density heatmaps, and entry-to-purchase conversion metrics. Deliverables include well-documented code supporting both recorded footage and live RTSP streams, demo instructions, CSV/JSON outputs per time slice, density visualisations, and a performance report covering tracking accuracy and staff filtering methodology. Ready to start immediately.

@amirrmusavifr

Hi, I’m an AI expert with professional experience in computer vision, with a proven track record of working on complex image processing and AI/ML model development. With skill sets: • Algorithm Development: Strong understanding of computer vision algorithms and techniques, including convolutional neural networks (CNNs), object detection, image segmentation and feature extraction. • Model Training & fine-tuning: Develop and train machine learning models tailored for image analysis and visual data interpretation. I have worked on some well-known models like YOLO, RCNN, U-Net, Deeplab, ViT etc. • AI Integration: Implement and integrate AI models into existing software and hardware systems, ensuring high performance and scalability. • Data Analysis: Analyze and process large datasets of images and video feeds to identify patterns, trends, and insights. • Data Handling: Experience in handling and processing large datasets, including image and video data. Familiarity with data augmentation techniques and synthetic data generation. • Performance Optimization: Optimize algorithms and models for real-time processing and ensure they can handle large-scale data efficiently. • Programming Skills: Proficient in programming languages such as Python. Experience with deep learning frameworks like TensorFlow, PyTorch, or Keras. • Tools & Libraries: Proficiency with OpenCV, scikit-image, and other relevant libraries. Experience with version control systems like Git.

@ekagrasingh

Hi, I have 8+ years of experience in Data Science. The solution will include: • YOLOv8-based person detection and tracking using ByteTrack • Cross-camera identity preservation using a Re-ID module to minimize duplicate counting across overlapping camera views • Staff filtering mechanism to exclude employees from customer analytics • Footfall counting, crowd-density heatmaps, and entry-to-purchase conversion analytics • Support for both recorded video files and live RTSP camera streams Deliverables: 1. Clean, modular, and well-documented Python code. 2. Setup instructions and guidance for testing on your own camera feeds. 3. Sample output files in CSV/JSON format along with density visualizations. 4. Optional notebook/dashboard for reviewing analytics. 5. Brief performance report covering tracking accuracy and staff-filtering methodology. The implementation will focus on accuracy, reproducibility, and clear documentation, in line with the acceptance criteria. I would be happy to discuss camera setup details and any assumptions regarding purchase-conversion measurement before starting. Thank you for your consideration. Best regards, Ekagra Singh

@rakhshanz3

With nearly two decades of experience spanning academia and the technology industry, I'm confident I can successfully take on your project. Holding a Bachelors in Computer Science, a PhD in Artificial Intelligence, and having previously served as a lecturer, my foundation in teaching and research complements my problem-solving Drawing from this background, I can assure you that accuracy and detailed documentation are my top priorities. My past work developing end-to-end technical solutions, which demanded strong understanding of APIs, cloud deployment and database management aligns well with your project requirements. I can build a Python pipeline using YOLOv8 for object detection, ByteTracker + Re-ID for multi-camera tracking and perform staff filtering to give reliable foot traffic counts, density visualizations and conversion figures using the same. My system will be well-structured with clear documentation to ensure easy replication on your own cameras. Choosing me means choosing a seasoned professional who gets things done efficiently without ever compromising on the quality. Let's discuss further how we can leverage AI for your retail metrics needs!

@Geetam00

With a proven track record of building end-to-end solutions and a wide range of expertise that aligns perfectly with your requirements, I am confident in my ability to deliver a robust Python pipeline for your Retail People Tracking & Analytics project. My background in Data Analysis and Visualization will enable me to efficiently implement the YOLOv8, ByteTracker, and Re-ID components you desire, guaranteeing precise detection and tracking of human subjects across CCTV streams. Identifying the actual customers separate from staff members is pivotal in deriving accurate retail metrics, and this is where my Machine Learning skills come into play. Utilizing intelligent algorithms, I can ensure that employee activities are not marked as customer behaviors and accurately calculate conversion figures for strategic decision-making. Additionally, my experience in architecting sophisticated software that handles large data sets securely and at scale will guarantee reliable foot traffic counting, density analysis generation, and consistency of entry-to-purchase conversion ratios. What sets me apart for this task boils down to two main factors - meticulousness and comprehensive documentation. I understand the significance of providing clearly structured code accompanied by detailed instructions or a demo dataset for you to replicate accurate results on your store's own cameras effortlessly.

@ToufeeqX

I HAVE DONE SOMETHING SIMILAR BEFORE! I understand the need for a clean, professional, and user-friendly Python pipeline for retail people tracking and analytics. Our expertise lies in developing seamless, integrated solutions using YOLOv8, ByteTracker, and Re-ID modules. You won’t find someone more aligned with what you’re looking for. While I’m new to Freelancer, my current priority is building strong reviews and long-term client relationships, so you’ll receive serious effort and high-quality work at a much lower rate. Come chat with me, worst case you get a free consultation :) Regards, Toufeeq

@simonj29

I can build a complete Python retail analytics pipeline using YOLOv8, ByteTrack, and a reliable Re-ID model. The solution will process recorded videos or live RTSP streams, detect people only, maintain stable IDs within each camera, and match the same shopper across multiple cameras to reduce duplicate counting. Staff will be excluded from customer statistics using configurable methods such as staff image enrollment, Re-ID profiles, uniform classification, and staff-only zones. Key outputs will include: • Unique visitor and foot-traffic counts • Entry and exit totals by time interval • Occupancy and dwell-time statistics • Crowd-density heatmaps • Staff-filtered customer metrics • Entry-to-purchase conversion • CSV or JSON reports Purchase conversion can be calculated using checkout-zone activity or POS events, depending on the available data. Deliverables will include documented Python code, YOLOv8 detection, ByteTrack tracking, cross-camera Re-ID, staff filtering, configurable zones and counting lines, sample data or testing instructions, output examples, visualisations, and an optional dashboard or notebook. I will also provide a performance report covering tracking accuracy, ID switches, duplicate-count reduction, staff-filtering results, FPS, and known limitations.