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Object Detection Models

Open‐source deep learning models specialized in detecting and localizing objects in images and videos.

6 projects

25,507 contributors

$6.7M

Ultralytics YOLO

Ultralytics YOLO11 🚀

Contributors

12,385

Organizations

803

Software value

$3.6M

YOLOv5

YOLOv5 is a computer vision model and framework for real-time object detection, offering state-of-the-art performance, easy training and deployment capabilities, and extensive documentation. It implements the YOLO (You Only Look Once) architecture with improvements for speed and accuracy.

Contributors

8,823

Organizations

703

Software value

$804K

Detectron2

Detectron2 is a computer vision library developed by Facebook AI Research (FAIR) that implements state-of-the-art object detection algorithms. It provides a modular, flexible platform for implementing and training computer vision models, with support for tasks like object detection, instance segmentation, keypoint detection, and panoptic segmentation.

Contributors

4,299

Organizations

601

Software value

$2.3M

DeepLabCut

Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans

This project hasn't been onboarded to LFX Insights.

PaddleSeg

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.

This project hasn't been onboarded to LFX Insights.

Ultralytics YOLOv3: PyTorch to TFLite Conversion

YOLOv3 in PyTorch > ONNX > CoreML > TFLite

This project hasn't been onboarded to LFX Insights.
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