opencv/opencv_zoo resource

Health v2 · maintenance only

Adoption not part of the score

1034 stars · 299 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of pre-trained computer vision models tuned for OpenCV's DNN inference module, accompanied by benchmarking tools for various hardware platforms. It provides demo scripts and performance measurements across x86 CPUs, ARM boards, NPUs, and GPUs.

Use cases

• run face detection with opencv dnn
• benchmark deep learning models on raspberry pi
• find pretrained models for opencv inference
• run object detection on embedded arm boards
• compare model inference speed across npu hardware
• deploy computer vision models without pytorch or tensorflow

When to choose

• you want lightweight inference using only OpenCV without heavy ML frameworks
• you need benchmark data for vision models on edge devices like Jetson or Raspberry Pi
• you want ready-to-use pretrained models with demo scripts for common vision tasks

When to avoid

• you need to train or fine-tune models rather than run inference
• you require models beyond the curated vision tasks included in the zoo
• you need production model serving with REST APIs rather than library-style inference

Facets

dataset · maturity active

machine-learning deep-learning computer-vision image-processing benchmarking llm-inference computer-vision machine-learning deep-learning developer-tools performance python cross-platform windows embedded opencv-dnn model-zoo pretrained-models inference edge-devices npu face-detection object-detection quantization linux macos gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="opencv/opencv_zoo")