You will get Image Segmentation & Semantic Segmentation AI Model (OpenCV) python
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Project details
As a computer vision and machine learning engineer, my expertise lies in image semantic segmentation using cutting-edge techniques such as vision transformers like ViTs Segformer and Swin Transformer, as well as CNNs like DeepLabV3+, U-Net, YOLO, YOLOv8. Applications across industries, including medical imaging, autonomous vehicles, aerial imagery, satellite imagery analysis.
SPECIALIZED WORK
Flood detection and disaster management using semantic segmentation techniques (ViTs).
Computer Vision OpenCV, Image Classification, Semantic Segmentation
Object Detection YOLO, Object Tracking, Object Recognition, Emotion Recognition, Facial Recognition
Deep Learning (DeepLabV3+ Unet CNN YOLO GANs)
Vision Transformers for semantic segmentation (ViTs Segformer, Swin Transformer)
Semantic Segmentation of Remote Sensing Imagery, Biomedical imagery
TensorFlow PyTorch Karas OpenCV, Hugging Face, Mmsegmentation PyCharm
#ComputerVisionEngineer #MachineLearningEngineer #ImageProcessing #OpenCV #ObjectDetection #YOLO #SemanticSegmentation #DeepLabV3+ #UNet #SwinTransformer #Segformer #MachineLearning #PythonScript #ObjectDetectionTracking #ObjectDetection #TensorFlow #PyTorch #CV #ML
SPECIALIZED WORK
Flood detection and disaster management using semantic segmentation techniques (ViTs).
Computer Vision OpenCV, Image Classification, Semantic Segmentation
Object Detection YOLO, Object Tracking, Object Recognition, Emotion Recognition, Facial Recognition
Deep Learning (DeepLabV3+ Unet CNN YOLO GANs)
Vision Transformers for semantic segmentation (ViTs Segformer, Swin Transformer)
Semantic Segmentation of Remote Sensing Imagery, Biomedical imagery
TensorFlow PyTorch Karas OpenCV, Hugging Face, Mmsegmentation PyCharm
#ComputerVisionEngineer #MachineLearningEngineer #ImageProcessing #OpenCV #ObjectDetection #YOLO #SemanticSegmentation #DeepLabV3+ #UNet #SwinTransformer #Segformer #MachineLearning #PythonScript #ObjectDetectionTracking #ObjectDetection #TensorFlow #PyTorch #CV #ML
Machine Learning Tools
BERT, ChatGPT, MATLAB, NLTK, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, SciPy, TensorFlowWhat's included
| Service Tiers |
Starter
$45
|
Standard
$120
|
Advanced
$220
|
|---|---|---|---|
| Delivery Time | 2 days | 5 days | 8 days |
Number of Revisions | Unlimited | Unlimited | Unlimited |
Number of Graphs/Charts | 5 | 8 | 10 |
Model Validation/Testing | - | - | - |
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
Frequently asked questions
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PL
Prasanna M L.
Jun 29, 2026
Data Annotators Trainer for AI Projects (Healthcare/General Domain)
It was a pleasure working with Muhammad. He has a strong understanding of data annotation concepts and explains both the fundamentals and practical aspects using real-world examples and industry tools. He is highly responsive, communicates clearly, and is always willing to help resolve questions quickly. I appreciate his support and look forward to working with him again in the future.
OL
Omar L.
Mar 30, 2026
Image Annotation for YOLO Training: Ice Hockey Shooting Frames
EM
Erin M.
Jan 30, 2026
Machine Learning Data Labelers Needed — 10–15 min Survey + 30 min Focus Group ($40)
Muhammad provided helpful input on our project. He communicated clearly and promptly and fully completed each task.
AA
Ahmed A.
Sep 9, 2025
Experienced Medical Image Annotation Expert (MRI & CT Scans)
The expert delivered precise and accurate annotations with great attention to detail. Communication was clear and responsive throughout, and he used RoboFlow very professionally. Truly an expert in data annotation—highly recommended!
About Muhammad Sibtain
Expert Data Annotation & Image Labeling | Semantic Segmentation, CVAT
100%
Job Success
Ahmadpur Sial, Pakistan - 2:44 pm local time
I specialize in semantic segmentation, instance segmentation, and object detection for medical imaging, retail analytics, sports technology, and electronics schematics. Whether you need brain MRI DICOM annotation, retail SKU labeling, sports player tracking, or electronic component segmentation—I deliver pixel-perfect datasets.
My Quality Guarantee as a Data Quality Specialist:
Every batch undergoes multi-stage manual audit to ensure 100% adherence to your labeling guidelines. I verify all exports (YOLO, COCO JSON, Pascal VOC, XML) in target environments for immediate import-readiness.
Specialized Workflows I Master:
* Semantic & Instance Segmentation: Pixel-perfect masks using polygons and brushes
* Object Detection: High-speed bounding boxes for YOLO (v5-v11)
* 3D Point Cloud & LiDAR: Precise cuboid placement for autonomous driving
* Video & Temporal Tracking: Frame-by-frame with consistent object IDs
* Keypoint & Landmark: Sub-pixel accuracy for pose estimation
Industry-Specific Data Annotation:
* Medical AI: MRI, CT, X-Ray, Ultrasound (HIPAA-aware)
* Retail Data Quality: SKU-level tagging, smart shelf annotation, product recognition
* Sports Analytics: Player tracking, ball detection, pose estimation, field segmentation
* Electronics & Schematics: Component labeling, PCB annotation, circuit diagram segmentation
* Automotive: Lane detection, pedestrian tracking, edge-case scenarios
* Agriculture/GIS: Aerial mapping, crop health analysis, polygon annotation
Tools I Use:
CVAT, Label Studio, Labelbox, Roboflow. I can master your proprietary platform within 24 hours.
Formats I Deliver:
YOLO, COCO JSON, Pascal VOC XML, CSV, and custom formats.
I am built for scale — 100 images or 100,000. Ready to clean your training data?
Click "Message" to discuss your project or request a free sample task.
Steps for completing your project
After purchasing the project, send requirements so Muhammad Sibtain can start the project.
Delivery time starts when Muhammad Sibtain receives requirements from you.
Muhammad Sibtain works on your project following the steps below.
Revisions may occur after the delivery date.
Initial Consultation and Requirement Gathering
This step involves discussing project goals, technical requirements, and any specific details that will guide the project development.
Data Preparation and Exploration
This includes data cleaning, normalization, and preliminary analysis to understand the dataset's characteristics and potential challenges.