You will get "Bounding Box & Polygon Image Annotation for YOLO & Object Detection"
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Project details
I am specialize in providing high-quality image annotation and dataset preparation services for computer vision and machine learning projects. With my proficiency in tools like LabelImg, Label Studio, CVAT and Roboflow, I guarantee accurate annotations that meet your needs. I provide datasets in YOLO, COCO JSON, and Pascal VOC formats, whether they be bounding boxes, polygons, or keypoints.. My careful approach guarantees accuracy and consistency which helps you build reliable AI models. Allow me to help you transform raw images into useful datasets with fast turnaround times and attention to detail.
Machine Learning Tools
Microsoft Excel, NumPy, OpenCV, pandas, Python, PyTorch, TensorFlowWhat's included
| Service Tiers |
Starter
$30
|
Standard
$80
|
Advanced
$150
|
|---|---|---|---|
| Delivery Time | 2 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 0 | 1 | 3 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$20 - $60
Additional Revision
+$10
Additional Model Variation
(+ 2 Days)
+$30
Additional Scenario
(+ 2 Days)
+$35
Additional Graph/Chart
+$10
Model Documentation
(+ 1 Day)
+$35
Data Source Connectivity
(+ 2 Days)
+$40
Source Code
+$70
Custom Dataset Augmentation
(+ 2 Days)
+$45
Post-Training Support
(+ 2 Days)
+$50Frequently asked questions
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April Joy D.
Aug 6, 2025
Seeking Diagnostics Lab Professionals- $20 Paid Survey
Thank you, Taufia!
AM
Aleksa M.
Jun 25, 2025
Single-image sphere reconstruction
About Taufia
PhD in Computational Biology - AI, ML & Scientific Data Analysis
100%
Job Success
Rostock, Germany - 8:08 pm local time
Alongside my research and computational work, I have experience teaching and mentoring students and researchers in biological data analysis, Python, statistics, machine learning and computational research methods. I particularly enjoy helping researchers understand not only how to use computational tools, but also why a particular analytical or machine-learning approach is appropriate for their scientific question.
My expertise spans computational biology, bioinformatics, machine learning, scientific image analysis, cheminformatics, protein modeling and data visualization. I also have extensive experience working with fluorescence microscopy, calcium imaging, electrophysiology datasets and high-dimensional biological data.
Key Areas of Expertise
• Computational Biology & Bioinformatics
• Machine Learning & AI for Biological Data
• AI Systems & Knowledge Engineering
- Agentic AI Workflows
- Retrieval-Augmented Generation (RAG)
- AI Memory & Knowledge Systems
- Scientific AI Applications
- Research Automation
- AI Workflow Architecture
• Scientific Python Development (Pandas, NumPy, Scikit-learn, PyTorch)
• Data Analysis, Statistics & Visualization
• Image Processing & Quantitative Microscopy
• Cheminformatics & Protein Modeling
• Computational Neuroscience & Electrophysiology
• Research Automation & Scientific Software Development
Selected Research & Technical Projects
• Developed reproducible Python pipelines for fluorescence imaging and quantitative biological data analysis.
• Designed machine-learning workflows for biological and physiological datasets.
• Conducted bioinformatics analyses involving genomic and VCF-based datasets.
• Developed AI-assisted approaches for fluorescence microscopy and scientific image analysis.
• Applied statistical modeling to investigate calcium dynamics and muscle physiology in Drosophila flight systems.
• Built scientific software for data visualization, analysis, and workflow automation.
• Developed and taught computational workflows that help researchers understand and independently analyze biological datasets.
• Co-founded DataLens.Tools, where we develop AI-powered tools and workflows for scientific research and data analysis.
I have authored peer-reviewed scientific publications and presented research at international conferences. I enjoy collaborating on interdisciplinary projects at the intersection of biology, AI, data science and scientific computing.
I am particularly interested in projects where researchers need more than a black-box analysis, whether that means developing a reproducible computational workflow, validating a machine-learning approach, building a scientific AI system or helping a research team understand and adopt computational methods.
If you are working with complex biological data or exploring how AI, machine learning or scientific computing could support your research, I would be happy to connect.
Steps for completing your project
After purchasing the project, send requirements so Taufia can start the project.
Delivery time starts when Taufia receives requirements from you.
Taufia works on your project following the steps below.
Revisions may occur after the delivery date.
Review Dataset and Requirements
Analyze the dataset provided and confirm annotation requirements, including formats, object categories, and labeling guidelines.
Begin Image Annotation
Annotate images using LabelImg based on the agreed requirements, ensuring precision and quality for each object category.