A fast, easy-to-use, production-ready inference server for computer vision supporting deployment of many popular model architectures and fine-tuned models.
-
Updated
May 14, 2024 - Python
A fast, easy-to-use, production-ready inference server for computer vision supporting deployment of many popular model architectures and fine-tuned models.
Darknet/YOLO object detection framework
Collection of Python tutorials on computer vision accompanying the “Bird by Bird Tech” series of articles.
NetworkOptix open-source components used to build Powered-by-Nx products including Desktop Client for Network Optix Video Management Platform.
NVR with realtime local object detection for IP cameras
Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.
Open source Python library for building bioimage analysis pipelines
Fast and Accurate ML in 3 Lines of Code
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
We write your reusable computer vision tools. 💜
Notebooks to upload/download marine footage, connect to a citizen science project, train machine learning models and publish marine biological observations.
Neural Network Compression Framework for enhanced OpenVINO™ inference
Simplify camera trap image analysis with ML species recognition models based around the MegaDetector model
autoupdate paper list
Gather research papers, corresponding codes (if having), reading notes and any other related materials about Hot🔥🔥🔥 fields in Computer Vision based on Deep Learning.
Repositorio de tesis de maestría para la localización y detección de daño pulmonar causado por COVID19.
OpenMMLab Detection Toolbox and Benchmark
The open-source tool for building high-quality datasets and computer vision models
Hierarchical perception library in Python for pose estimation, object detection, instance segmentation, keypoint estimation, face recognition, etc.
OpenMMLab YOLO series toolbox and benchmark. Implemented RTMDet, RTMDet-Rotated,YOLOv5, YOLOv6, YOLOv7, YOLOv8,YOLOX, PPYOLOE, etc.
Add a description, image, and links to the object-detection topic page so that developers can more easily learn about it.
To associate your repository with the object-detection topic, visit your repo's landing page and select "manage topics."