You will get High-Quality Annotated Dataset for Computer Vision Model Training
Project details
I provide high-quality annotated datasets for computer vision model training to help build accurate and reliable AI systems. My expertise includes labeling data for object detection, image segmentation, tracking, and classification using tools like Roboflow and Label Studio. I have experience working on real-world AI projects such as CCTV surveillance, wildlife monitoring, construction safety detection, retail analytics, warehouse automation, pose estimation, and medical imaging.
I deliver precise annotations including bounding boxes, polygons, segmentation masks, keypoints, and polylines with strong consistency and accuracy. Each dataset is properly organized with class definitions, train/validation/test splits, and YOLO format-compatible exports for smooth training and deployment.
I ensure high-quality datasets by handling real-world challenges like occlusion, motion blur, low light, and crowded scenes. My focus is to provide clean, structured, and production-ready datasets that improve model performance.
Fast communication, reliable delivery, and strong attention to detail are always guaranteed.
Regard:
Muhammad Ahsan
I deliver precise annotations including bounding boxes, polygons, segmentation masks, keypoints, and polylines with strong consistency and accuracy. Each dataset is properly organized with class definitions, train/validation/test splits, and YOLO format-compatible exports for smooth training and deployment.
I ensure high-quality datasets by handling real-world challenges like occlusion, motion blur, low light, and crowded scenes. My focus is to provide clean, structured, and production-ready datasets that improve model performance.
Fast communication, reliable delivery, and strong attention to detail are always guaranteed.
Regard:
Muhammad Ahsan
What's included
| Service Tiers |
Starter
$100
|
Standard
$170
|
Advanced
$250
|
|---|---|---|---|
| Delivery Time | 2 days | 2 days | 7 days |
Number of Revisions | 2 | 2 | 4 |
Number of Model Variations | 1 | 3 | 6 |
Number of Scenarios | 2 | 5 | 10 |
Number of Graphs/Charts | 1 | 4 | 6 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | ||
Source Code |
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JR
Joshua R.
Apr 24, 2026
Computer Vision Object Detection
AVOID them. Beware. You can provide clear job description and he will act like it isn't part of the job. I hired him mainly to detect playing cards. The code provided only detects some cards. He claims that it is out of scope of job to provide accurate card detection, which requires training in setting of cards, as he trained without the setting, and he claims fine tuning for accurate card detection and fixing color detection is not part of the job. Clearly it is part of the job because if cards are not detected, then job is not complete.
STAY AWAY.
They wouldn't continue the job until I paid them. So, I paid them. They then refused to finish the job.
I am now with codes that are basically useless to me and about $220 USD gone and plenty of hours and about 2 months of wait time.
Even the job said to integrate the CV code into the existing provided game mechanics code. They claimed that isn't part of the job.
So, be warned. They choose to determine what the job is. That's not how freelancing works.
STAY AWAY.
They wouldn't continue the job until I paid them. So, I paid them. They then refused to finish the job.
I am now with codes that are basically useless to me and about $220 USD gone and plenty of hours and about 2 months of wait time.
Even the job said to integrate the CV code into the existing provided game mechanics code. They claimed that isn't part of the job.
So, be warned. They choose to determine what the job is. That's not how freelancing works.
About Muhammad
Computer Vision Engineer | YOLO, Object Detection & Tracking | Edge AI
60%
Job Success
Khanewal, Pakistan - 3:06 am local time
What I do:
I handle the full pipeline, dataset prep, model training, optimization, and real-time deployment for object detection, tracking, segmentation, pose estimation, OCR, and video analytics. I specialize in deploying these models on edge devices (NVIDIA Jetson, embedded ARM systems) and optimizing them for low-latency, high-FPS inference using TensorRT, ONNX, and CUDA.
Tech stack:
Python, C++, OpenCV, PyTorch, TensorFlow, YOLOv5/v8/v11, Ultralytics, ONNX Runtime, TensorRT, CUDA, NVIDIA DeepStream, FastAPI/Flask
Recent use cases:
CCTV surveillance & video analytics, industrial/manufacturing inspection, ANPR & license plate recognition, retail analytics, traffic & smart parking systems, drone vision, sports analytics
Where I deploy: Jetson Nano/Xavier/Orin, Raspberry Pi, embedded edge devices, Linux servers, cloud GPU infrastructure
If you're scaling a CV product, optimizing a YOLO pipeline, or need a model that actually performs outside the lab, let's talk about your project.
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Project Kickoff & Requirements
Client purchases the project and shares all requirements, including data details, objectives, and instructions to start the work smoothly and ensure accurate delivery.
Project Execution & Progress
I complete the project step by step according to the agreed process and update progress in the workroom so the client stays informed about every stage clearly.