OpenDetect

Open-source object detection for production Python applications.
Commercial-use friendly. Python API + CLI.

opendetect gives you one consistent interface for modern ONNX detectors across CPU and accelerated runtimes.

Why OpenDetect

• Unified API across detector families
• Runtime-aware acceleration with ONNX Runtime
• Stable OpenCV/NumPy-first workflow for real video/image pipelines
• Built-in model registry, auto-download, and caching
• First-class CLI for inference, benchmarking, and model management

Install

pip install opendetect

Optional extras:

pip install "opendetect[cpu]"
pip install "opendetect[gpu]"
pip install "opendetect[tensorrt]"

Quickstart (Python)

import cv2
from opendetect import Detector

detector = Detector(model="rfdetr-m")

image = cv2.imread("input.jpg")
detections = detector.predict(image, color="bgr")
annotated = detector.annotate(image, detections, color="bgr")

cv2.imwrite("output.jpg", annotated)

File helpers:

from opendetect import Detector

detector = Detector(model="yolox-s")
detector.infer_image_file("input.jpg", output_path="output.jpg")
detector.infer_video_file("input.mp4", output_path="output.mp4", max_frames=300)

Quickstart (CLI)

opendetect-infer --image input.jpg --model-id rfdetr-m --output output.png
opendetect-infer --video input.mp4 --model-id yolox-s --tensor-rt --output output.mp4
opendetect-benchmark --model-id rfdetr-l --mode dummy --warmup 20 --iterations 200
opendetect-models list

Runtime Support

OpenDetect uses ONNX Runtime execution providers and selects the best available runtime automatically:

• CPU
• CoreML (Apple Silicon / macOS)
• CUDA
• TensorRT
• DirectML
• OpenVINO
• ROCm / MIGraphX

TensorRT note:

• opendetect[tensorrt] installs Python dependencies only.
• A compatible system TensorRT/CUDA stack is still required.

Model Families

Family	Year	License
RF-DETR	2026	Apache-2.0
ByteTrack Detector	2022	MIT
RTMDet	2022	Apache-2.0
YOLOX	2021	Apache-2.0

Documentation

Hosted docs:

• https://opendetect.readthedocs.io

Full guides are in docs/:

• Start here: docs/index.md
• Installation and runtimes: docs/getting-started/installation.md, docs/getting-started/runtimes.md
• Python and CLI usage: docs/getting-started/python.md, docs/getting-started/cli.md
• Benchmarks: docs/guides/benchmarks.md

Build docs locally:

pip install -r docs/requirements.txt
make -C docs html

License

Apache License 2.0 (LICENSE).