YOLO Mussel Cluster Detector

@johnedwardl

Hi, I will train a custom YOLO model (likely YOLOv8 or YOLOv12) to detect and track mussels in real-time video, ensuring it can distinguish between individual mussels and clusters. With over 5,000 images at our disposal, I will implement a robust training strategy optimized for performance, achieving at least 15 FPS on a standard NVIDIA GPU. My previous experience with similar projects gives me a clear view of the architecture needed to maintain high precision and recall for both classes. I will deliver the final weights and inference script compatible with PyTorch, along with thorough documentation detailing hyperparameters and a comprehensive performance report that includes precision, recall, and mAP metrics. To ensure smooth integration, I’ll provide a README with clear instructions for reproducing the results on your side. Once the model consistently counts and tracks mussels accurately, we’ll be ready to finalize this project. Thank you.

@OBRY8246

Hello, I am excited about the opportunity to develop a custom YOLO model specifically for detecting and tracking mussels in real-time video feeds. With over 5,000 images at your disposal, I'll ensure that the model accurately distinguishes between individual mussels and clusters, maintaining at least 15 FPS on a standard NVIDIA GPU without sacrificing accuracy. My approach will focus on: - **Real-time Performance**: Optimizing the model for live camera feeds so that it can process data swiftly, crucial for your monitoring needs. - **Counting & Tracking**: Implementing a robust tracking system that assigns consistent IDs to individual mussels, ensuring every movement is accurately recorded over time. - **High Confidence**: Striving for high precision and recall in the classification of both individual mussels and clusters. Deliverables will include final weights, a detailed training script, performance metrics, and thorough documentation to ensure you can replicate the results seamlessly. How does your dataset specify the labeling for clusters vs individual mussels? Best regards,

@haseebsidd07

Hey , I just went through the project description, and I see you are looking for someone experienced in Deep Learning, Machine Learning (ML), C++ Programming, Algorithm, Image Processing, YOLO, Computer Vision, Geospatial, Python and Object Detection. It instantly reminded me of a client who faced similar challenges, and I knew I had a tailor-made solution for it. Please review my profile to confirm that I have great experience working with these tech stacks. While I have few questions: • Is there anything else you’d like to add to the project details? • What’s the top hurdle you’re facing with this project? • What is the timeline to get this done? Why Choose Me? 250+ Projects. 5 Years. Zero Misses. My reputation is built on a single metric: Flawless Execution. While others promise quality, my last 100+ consecutive 5-star reviews prove it. I don’t just finish the job; I set the standard. Timings: 9am - 9pm Eastern Time (I work as a full time freelancer) The portfolio here is just the tip of the iceberg. To respect client confidentiality, my recent heavy-hitters aren't public, but I can share them 1-on-1. Click the 'CHAT' button, and I’ll send over the relevant samples immediately for your review. Regards, Abdul Haseeb Siddiqui.

@luisn61

Hello, With a deep understanding of AI and extensive experience in the Python ecosystem, I am perfectly suited to deliver your Mussel Cluster Detector project. Over the years, I have built numerous object detection models using various versions of YOLO, including the ones you've mentioned: YOLOv8, YOLOv11, and the newer YOLOv12/v26. Rest assured, our choice would be guided by the specific requirements and constraints in this task. Working with educational & research clients like yourself has equipped me with the ability to comprehend and cater to nuanced project needs methodically. My proficiency in backend technologies suits your request for compatible PyTorch or Ultralytics CLI delivery. Most importantly, I've consistently delivered impressive real-time performances while ensuring high accuracy and precision as crucially required in your project. Finally, my track record aligns with your expectation for clear documentation and strong post-project support. My previous work on research data processing, machine learning applications in academics, and reproducible workflows will all contribute to a comprehensive training kit enabled by clean code that facilitates thorough analysis and precise reproduction of the results on your end. Let's transform your unique dataset into a high-accuracy and efficient Mussel Cluster Detector system together! Thanks!

@josephc597

Hello, Being a specialist in AI integration and automation, I am confident in my ability to develop your YOLO model accurately and efficiently with my expertise in PyTorch and YOLO series - be it v8, v11 or the latest v12/v26. I have a proven track record of building real-time AI models capable of distinguishing between diverse classes on live camera feeds, just like your project requires. Moreover, my proficiency extends to object tracking, ensuring consistent IDs for individual mussels even across frames for accurate counting. On top of this, I hold a strong grasp on related performance metrics like precision, recall, mAP, which I'll provide along with necessary documentation. And who can ignore the power of clearly written instructions in a README file? You'll find my README impeccable and easy-to-follow. My work is characterized by a deep appreciation of balancing accuracy with real-time performance without compromising either facet. My dedication to long-term thinking positions me perfectly to meet your project's high demands for speed, security and scalability. Let me build you a game-changing AI+live video monitoring system; together we can detect even lost mussels at 15+ FPS! Thanks!

@janj89

Hello, With my solid experience as a Senior Full Stack Developer over the past 8 years, I have honed my skills in various technologies and developed an exceptional track record of building robust, highly-responsive applications. In terms of your YOLO Mussel Cluster Detector project, I bring ample expertise in Python -a key language to effectively train the custom YOLO model you require. In addition to Python, I also boast comprehensive knowledge in backend technologies and cloud-based solutions like Docker, AWS, CI/CD pipelines and serverless architecture. These skills enable me to ensure a seamless integration of your YOLO model with other components while optimizing the system's performance. Moreover, my career span has exposed me to diverse industries, allowing me to draw insights and unique solutions for your specific needs. By choosing me for this project, you'll gain access to a developer who is meticulous when it comes to producing performance reports and documentation. Lastly, I pride myself on my ability to deliver projects that not only meet objectives but exceed expectations - exactly what I intend to do with yours. Thanks!

@mikaels79

Hello, As a YOLO model expert, I feel confident in bringing my Python skills and extensive experience in building real-time object detection systems to this project. Over the years, I have devoted myself to creating robust models that excel in accuracy and speed, which will be vital to your YOLO Mussel Cluster Detector. With my specialization in JavaScript and its modern ecosystems, I assure you an efficient and scalable solution that aligns with your project requirements. Handling complex datasets is not new to me; I am well versed in handling over 5,000 images for labeling, training, and exploiting data augmentation techniques to maximize your model's potential. To supplement your requirements, I can provide you with detailed training documentation at the end of this project so you can reproduce the results easily. Additionally, I'll furnish you with a comprehensive Performance Report including key metrics - Precision, Recall, mAP - and a sample video summarizing the tracking outputs. User-experience is crucial in every implementation; my proficiency in React.js and GraphQL can further enhance the UI/UX design of your system. As we collaborate on this endeavor, rest assured that clear communication and fast delivery will be my utmost priority. My goal is not just to meet your expectations but to exceed them, ensuring you have a reliable product that delivers consistently high-level performance in detecting and tracking every indi Thanks!

@tymoteuszs52

Hello, With my extensive experience and expertise in developing scalable, high-performance applications, I am confident that I am the perfect fit for your YOLO Mussel Cluster Detector project. One of my key strengths is my proficiency with Python, which will be paramount for customizing your YOLO model. Additionally, having tackled various complex projects in different industries, I understand the importance of accuracy without compromising real-time performance for live monitoring, a crucial requirement for your mussel tracking endeavor. Drawing from my experience as a Senior Full Stack Developer with a strong background in both frontend (React, Angular) and backend technologies (Python), I can provide comprehensive deliverables tailored to your needs. My understanding of cloud infrastructure like AWS is a relevant asset as it enables me to design a robust system that meets your specific project requirements. To ensure this collaboration runs smoothly, I commit to providing highly-detailed training documentation, insightful performance reports (including precision and recall metrics), and a clean README file containing easy-to-follow instructions for using the final weights and inference script. My goal is to make sure you can confidently reproduce the results on your end and consider the project completed successfully. Thanks!

@ayesha86664

Hi there! You are building a custom YOLO model for real-time mussel tracking and the real challenge is maintaining high FPS while accurately counting and tracking individual mussels—this is exactly where most projects lose reliability. I recently trained a YOLOv8 model for marine species detection, achieving 96% precision and stable ID tracking across video streams, leveraging PyTorch and Ultralytics workflows. This experience directly aligns with building a two-class system for mussels and clusters. I will set up the training pipeline, optimize hyperparameters for speed and accuracy, implement robust object tracking, and deliver a ready-to-run inference script along with full performance metrics and documentation. Check our work: https://www.freelancer.com/u/ayesha86664 Do you want the tracking IDs to reset per session or maintain continuity across multiple video feeds? I am ready to start — just say the word. Best Regards, Ayesha

@toqeer74

This project focuses on developing a custom YOLO model for real-time detection and tracking of mussels using live camera feeds. I will design the model to distinguish between single "mussel" objects and "group" clusters, achieving a balance between accuracy and speed, maintaining at least 15 FPS with high precision and recall. The process involves training on a dataset of over 5,000 images, ensuring reliable object tracking and ID consistency. Deliverables include comprehensive documentation and detailed performance reports. What's your deadline, when do you need this live?

@tanithk

Hey — saw your post about training a custom YOLO model for mussel cluster detection. The big pain point with these kinds of models is getting consistent performance when the lighting, water clarity, and camera angles change in the field. Quick question before I suggest an approach: Do you already have a labeled dataset for the mussel clusters, or do you still need help defining the classes and annotation rules? I’ve worked with YOLOv8+ on niche object detection problems before, where small objects and noisy backgrounds made training and validation tricky. If you send over your current images, labels, or any brief spec you have, I can review it and tell you what’s realistic for accuracy and training time.