You will get I will build a real-time pose estimation system using YOLOv8
Project details
You will get a clean, reliable real-time human pose estimation system built using YOLOv8-Pose. I focus on creating practical, well-structured solutions that are easy to understand, test, and integrate into real applications such as fitness tracking, exercise analysis, and movement evaluation.
I have hands-on experience working with computer vision and deep learning models, and I pay close attention to clarity, reproducibility, and usability. Instead of just delivering a model, I ensure the pipeline works smoothly on real images or videos and provide clear code with simple instructions. My approach is detail-oriented and transparent, making it easy for you to review results and request changes.
Whether you need pose estimation for research, prototyping, or a real-world use case, I aim to deliver a dependable system that matches your requirements without unnecessary complexity.
I have hands-on experience working with computer vision and deep learning models, and I pay close attention to clarity, reproducibility, and usability. Instead of just delivering a model, I ensure the pipeline works smoothly on real images or videos and provide clear code with simple instructions. My approach is detail-oriented and transparent, making it easy for you to review results and request changes.
Whether you need pose estimation for research, prototyping, or a real-world use case, I aim to deliver a dependable system that matches your requirements without unnecessary complexity.
Machine Learning Tools
NumPy, OpenCV, pandas, Python, PyTorch, R, scikit-learn, SQL, TensorFlowWhat's included
| Service Tiers |
Starter
$40
|
Standard
$90
|
Advanced
$150
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 0 | 1 | 2 |
Number of Scenarios | 1 | 2 | 2 |
Number of Graphs/Charts | 0 | 1 | 2 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
Frequently asked questions
About Nissi
Computer Vision & Machine Learning Engineer |Pose Estimation, 3D Recon
Kottayam, India - 5:12 am local time
-Building CV pipelines: pose estimation, object detection, segmentation, tracking.
-Training and troubleshooting ML models (PyTorch/TensorFlow).
-3D reconstruction work on SDFs, neural implicit models, multi-view geometry.
-Image correspondence tasks using SIFT/SuperGlue.
-Creating simple, clean UIs for models (Gradio or React).
-Writing clear documentation and making projects reproducible.
I like keeping communication simple, sharing progress often, and making sure the final solution is something you can actually use and understand.
If you have an idea or dataset you want to explore, I’d be happy to help.
- Nissi :)
Steps for completing your project
After purchasing the project, send requirements so Nissi can start the project.
Delivery time starts when Nissi receives requirements from you.
Nissi works on your project following the steps below.
Revisions may occur after the delivery date.
Understand requirements and data
Review client inputs, clarify use-case, and finalize system scope.
Model setup and pose estimation
Configure and run YOLOv8-Pose for accurate keypoint detection.