Services

Hire a dedicated OpenCV developer to bring your computer vision application to the next level. Our consultants work as part of your existing development team (Agile/Scrum) or as a stand-alone resource, ensuring the highest standards of communication throughout the project.

OpenCV 5.0 shipped on June 4, 2026 — the first major release since 2018. It retires the legacy C API, requires C++17, removes the Caffe and Darknet importers, and replaces the DNN engine. Every long-lived OpenCV codebase now has a migration in its future, and we have already done the work. See our OpenCV 5 migration services.

OpenCV 5 migration and modernization

• OpenCV 5 migration — audit of 3.x/4.x codebases, C API and removed-module inventory, staged port, accuracy and latency parity testing (details)
• Porting legacy readNetFromCaffe / readNetFromDarknet pipelines to ONNX and the OpenCV 5 DNN engine
• Rebuilding with opencv_contrib for ml, G-API, Haar cascades, HOG and the xfeatures2d descriptors that left the main repository

Languages and platforms

• C++ (C++17 and later), Python (NumPy 2.x), and Java OpenCV development
• OpenCV on Android and iOS — the official Android SDK published to Maven Central (including the 16 KB page-size builds Google Play now requires), and the iOS framework with Swift and Objective-C bindings
• Embedded and edge vision on NVIDIA Jetson (Orin Nano/NX/AGX, Jetson Thor), Raspberry Pi 5 + AI Kit/AI HAT+, and NPU-accelerated SBCs — including lifecycle planning around the 2026 Jetson LPDDR4 module phase-outs
• NVIDIA CUDA module development and TensorRT engine integration

Deep learning and machine learning

• Deep-learning vision — PyTorch, ONNX Runtime, TensorRT, OpenVINO, LiteRT (the renamed TensorFlow Lite); YOLO-family detectors (YOLO26), vision transformers, and OpenCV 5's new DNN engine
• Model selection, training, fine-tuning and evaluation — classical ML through modern deep learning and vision-language models
• Quantization and distillation for edge deployment (FP16, INT8, QDQ graphs)
• OCR — Tesseract alongside OpenCV's DNN text detection/recognition and VLM-based document reading

Core computer vision

• Object detection, recognition, tracking and pose estimation
• Scene analysis and video analytics (real time or post-processing)
• Still-image and video capture pipelines (GStreamer, V4L2, industrial cameras)
• Camera calibration, stereo depth, structure-from-motion and point-cloud processing (OpenCV 5's calib, stereo, geometry and ptcloud modules)
• Feature detection and matching — SIFT/ORB through OpenCV 5's learned ALIKED, DISK and LightGlue pipeline
• Template matching, color matching, thresholding, edge detection, morphology and image normalization
• Pattern recognition and classical image processing

... and much more. Contact us to talk through your project.