You will get Computer vision, OCR, text recognition via OpenCV and Neural Networks
Top Rated
Project details
You will get optimized COmputer VIsion solution that will save you a lot of time and effort compared to an 'entry level' computer VIsion freelancer, I already know all possible pitfalls and can predict and avoid them to be 3-5 time more effective.
Happy to help with:
Computer vision: C++, Python, OpenCV, CUDA, Git, Linux, Qt, Boost, OpenGl, PCL, Strong math background.
Machine learning:
• C++, Python, OpenCV, CUDA, Git, Linux, Qt, Boost, OpenGl, PCL, SLAM, Strong math background
Hardware expert:
• Nvidia Jetson Nano, TX2, Xavier;
• Raspberry Pi;
• Arduino, STM32;
• Depth cameras like intel realsense d435i, etc.
• Lidars, Radars.
Machine learning engineer;
• C++, Python, OpenCV, CUDA, Linux, Darknet, SegNet, TensorFow
Happy to help with:
Computer vision: C++, Python, OpenCV, CUDA, Git, Linux, Qt, Boost, OpenGl, PCL, Strong math background.
Machine learning:
• C++, Python, OpenCV, CUDA, Git, Linux, Qt, Boost, OpenGl, PCL, SLAM, Strong math background
Hardware expert:
• Nvidia Jetson Nano, TX2, Xavier;
• Raspberry Pi;
• Arduino, STM32;
• Depth cameras like intel realsense d435i, etc.
• Lidars, Radars.
Machine learning engineer;
• C++, Python, OpenCV, CUDA, Linux, Darknet, SegNet, TensorFow
Machine Learning Tools
Azure Machine Learning, ChatGPT, Google AutoML, MLflow, NumPy, NVIDIA AI Platform, OpenCV, Python, PyTorch, Tesseract OCR, Vertex AIWhat's included
| Service Tiers |
Starter
$300
|
Standard
$1,000
|
Advanced
$10,000
|
|---|---|---|---|
| Delivery Time | 1 day | 3 days | 10 days |
Number of Revisions | 1 | 2 | 4 |
Model Validation/Testing | |||
Model Documentation | - | - | |
Data Source Connectivity | - | - | |
Source Code | - |
21 reviews
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VF
Victor F.
May 18, 2026
Proof of concept app in Python with OCR and AI functionality to scan book covers
VV
Viktoria V.
May 14, 2026
Windows App Solution Architect/Consultant
Working with Andrey and his team was excellent. We are pleased with the quality and speed of development. We encountered no difficulties during our collaboration. Andrey was always available and responded quickly to inquiries. We highly recommend working with him and will definitely be using him again!
VC
Victor C.
Nov 2, 2025
Object Detection, Tracking, and Range Calculations with OpenCV, YOLO, and ByteTrack
We needed help with choosing the right software (OpenCV, YOLO, etc) and hardware (Jetson Orin) for a machine vision project that includes object identification and tracking. Andrii made excellent recommendations and asked the right questions to identify requirements which we missed entirely.
Andrii is responsive, knowledgeable, and has experience with large software companies, which makes him a breeze to work with.
We will work with Andrii in the future if the opportunity arises.
Andrii is responsive, knowledgeable, and has experience with large software companies, which makes him a breeze to work with.
We will work with Andrii in the future if the opportunity arises.
MK
Maksim K.
Jun 8, 2025
AI reasearch
VC
Victor C.
Apr 27, 2025
60 minute consultation
Had a consultation regarding running YOLO models in C++. Andrii communicated in a timely and clear manner and has a good knowledge of the Machine Vision ecosystem.
About Andrii
AR | AI | Computer Vision | OCR | Neural Network | Mobile | OpenCV
100%
Job Success
Zaporizhzhia, Ukraine - 10:25 am local time
1. Computer vision
• C++, Python, OpenCV, CUDA, Git, Linux, Qt, Boost, OpenGl, PCL, Strong math background, Neural Networks
- road segmentation for unmanned vehicles (ENet, Caffe, OpenCV, C++, Linux)
- car tracking (Yolo v3, OpenCV, C++, Linux)
- wagon number identification (Yolo v4, Python)
- implementation of real time 360°/perspective camera transformation on Cuda (C++,
Cuda, OpenCV, Linux, Jetson Nano)
- distance calculation to point on 2D camera frame (C++, OpenCV, Linux)
- automate grading system for handwritten answer sheets (computer vision part, OpenCV,
Java, Android
Key stack: Linux, C++ (Qt), Python, Java, OpenCV, Yolo (darknet)
2. Machine Learning
Machine learning research projects in the following domains:
- person segmentation (ModNet, RVM, TDNet, UCTransNet, XMem etc.)
- image inpainting (Pen-Net, Deepfillv2, Shift-Net, ViNet etc.)
- image upscale (RDN, RRDN, Stable Diffusion, ISR etc.)
- image relighting (Total Relighting, DPR, RelightNet etc.)
- road segmentation for unmanned vehicles (ENet, Caffe, OpenCV, C++, Linux)
- car tracking (Yolo v3, OpenCV, C++, Linux)
- wagon number identification (Yolo v4, Python)
- implementation of real time 360°/perspective camera transformation on Cuda (C++,
Cuda, OpenCV, Linux, Jetson Nano)
- distance calculation to point on 2D camera frame (C++, OpenCV, Linux)
- automate grading system for handwritten answer sheets (computer vision part, OpenCV,
Java - Android, IOS - Swift)
Key stack: Linux, Python, Pytorch, Tensorflow, OpenCV, Pillow, Numpy, C++, CUDA, Darknet, SegNet
3. Robotics and Embedded development:
- OCPP Protocol, Linux, Modbus, Raspberry Pi, CAN;
-ROS Robot operating system;
- Skilled in SLAM, localization, mapping
- Experienced in path planning algorithms, obstacle avoidance, holonomic, and non-holonomic motion planning, trajectory planning for robotics arms;
- Used to work with Bayesian/Kalman filters, and sensor fusion (LiDAR, IMU, Visual, Odometry, Radar, GPS).
4. Android development (Kotlin, Java, Android Studio, Eclipse, Firebase).
Has expert colleagues in:
• .Net Framework (C#, VB.Net, ASP.Net, .Net Core, WPF, UWP,WCF, ADO.Net)
• Java (j2se, j2ee, servlets, java beans, Maven)
• JavaScript (Node.JS, Express.js, Vue.js, Element.js, Angular.js, D3.js)
• C++ (TCP/IP, HTTP, HTTPS, WebSocket, Modbus)
• Python (MAVLink, WebSocket)
• Step7 (S7 Communication, OCPP, Modbus, CANOpen, ProfiNet)
Database
• PostgreSQL
• MySQL
• MongoDB
• Microsoft SQL
• Oracle Database
• Neo4J
Software development for mobile platforms
• Crossplatform React Native, Flutter, Xamarin,
• Android (Kotlin, Java, Android Studio, Eclipse)
• iOS (Objective C, Swift)
Mobile apps development:
• Crossplatform: Futter, React Native, Xamarin.
• Android (Java, Kotlin)
• iOS (Objective C, Swift)
1. Native Development
- Kotlin/Java
- Swift / Objective-C
- iOS/macOS/tvOS/watchOS
- Firebase, CloudKit, Coredata
2. Cross-Platform and Hybrid App Development
- React Native/React
- Flutter / Dart
- Xamarin.iOS / Xamarin.Android / Xamarin.Forms
tech stack
● Android Studio, Gradle, Kotlin DSL, KSP
● Kotlin, Java programming languages
● AndroidX, Android Jetpack libraries, Android Architecture Components
● Jetpack Compose
● Material Design Components
● Clean Architecture, SOLID design principles
● MVVM, MVI, GoF design patterns
● Modularization (multi-module projects)
● Kotlin Coroutines + Flow, RxJava, RxBinding
● REST API / Networking - OkHttp, Retrofit 2, Socket IO
● Room Database, SQLite, Datastore
● Kotlinx Serialization, Protobuf, Moshi, Gson
● Dependency Injection (Hilt, Dagger 2, Koin)
● Git
● Firebase Products, Google Cloud APIs, HMS Services
● Admob, Google Play Billing Library (in-app purchases), Samsung/Huawei IAP
● Unit / Instrumented (UI) tests
● Agile Scrum development methodology
● CI/CD (GitHub Actions)
AR/VR:
Vuforia
ARkit/ARcore/AR Foundation
Wikitude
Oculus Integration
OpenXR
XR Interaction toolkit
VR Walkthrough
UltimateXR
VR Interaction Framework
Hardware expert:
• Nvidia Jetson Nano, TX2, Xavier;
• Raspberry Pi;
• Arduino, STM32;
• Depth cameras Intel Realsense d435i , Zed Sterelabs.
• Lidars, Radars.
Charging stations for the Electric Vehicles development software for the managing stations and networks (server and user applications):
• C#, SQL, PostgreSQL, .Net Core, REST Api, WebSockets
• OCPP Protocol, Linux, Modbus, Raspberry Pi
Software development
• .Net Framework (C#, VB.Net, ASP.Net, .Net Core, WPF, UWP,WCF, ADO.Net)
• Java (j2se, j2ee, servlets, java beans, Maven)
• JavaScript (Node.JS, Express.js, Vue.js, Element.js, Angular.js, D3.js)
• C++ (TCP/IP, HTTP, HTTPS, WebSocket, Modbus)
• Python (MAVLink, WebSocket)
• Step7 (S7 Communication, OCPP, Modbus, CANOpen, ProfiNet)
Database
• PostgreSQL
• MySQL
• MongoDB
• Microsoft SQL
• Oracle Database
• Neo4J
Steps for completing your project
After purchasing the project, send requirements so Andrii can start the project.
Delivery time starts when Andrii receives requirements from you.
Andrii works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery phase delivery