Model Type

Open Source Computer Vision Object Detection Models

The Roboflow Model Library contains pre-configured model architectures for easily training computer vision models. Just add the link from your Roboflow dataset and you're ready to go! We even include the code to export to common inference formats like TFLite, ONNX, and CoreML.

If you'd like to request a model we haven't yet implemented, please get in touch.

PyTorch Object Detection :: YOLOv7 TXT

YOLOv7

The latest in the YOLO mainline, from the creators of YOLOv4, YOLOv7 achieves state of the art performance on MS COCO amongst realtime object detectors. Read More...

YOLOv7 Tutorial YOLOv7 Repo YOLOv7 Colab Notebook

PyTorch Object Detection :: meituan/YOLOv6

MT-YOLOv6

MT-YOLOv6, or YOLOv6, is a high performance model in the YOLO family of models. Released in June 2022, it sets a new state of the art. Read More...

MT-YOLOv6 Tutorial MT-YOLOv6 Repo MT-YOLOv6 Colab Notebook

PyTorch Object Detection :: COCO JSON

YOLOS

YOLOS is a new transformer based object detection model. Read More...

YOLOS Tutorial YOLOS Repo YOLOS Colab Notebook

PyTorch Object Detection :: YOLOv5 TXT

YOLOv5

A very fast and easy to use PyTorch model that achieves state of the art (or near state of the art) results. Read More...

YOLOv5 Tutorial YOLOv5 Video YOLOv5 Repo YOLOv5 Colab Notebook

PyTorch Object Detection :: Pascal VOC

YOLOX

YOLOX is the winner of the most recent CMU Streaming Perception Challenge for its ability to tradeoff both edge inference speed and accuracy. Read More...

YOLOX Tutorial YOLOX Repo YOLOX Colab Notebook

PyTorch Object Detection :: YOLOv5 TXT

YOLOR

You Only Learn One Representation (YOLOR) is a state-of-the-art object detection model that pre-trains an implicit knowledge network and a set of parameters to represent explicit knowledge. Read More...

YOLOR Tutorial YOLOR Video YOLOR Repo YOLOR Colab Notebook

PyTorch Object Detection :: Scaled-YOLOv4

Scaled-YOLOv4

As of December 2020, Scaled-YOLOv4 is state-of-the art for object detection. Scaled-YOLOv4 implements YOLOv4 in the PyTorch framework with Cross Stage Partial network layers. Read More...

Scaled-YOLOv4 Tutorial Scaled-YOLOv4 Video Scaled-YOLOv4 Repo Scaled-YOLOv4 Colab Notebook

Tensorflow 2 Object Detection :: TFRecord

EfficientDet-D0-D7

A scalable, state of the art object detection model, implemented here within the TensorFlow 2 Object Detection API. Read More...

EfficientDet-D0-D7 Tutorial EfficientDet-D0-D7 Repo EfficientDet-D0-D7 Colab Notebook

Darknet Object Detection :: Darknet TXT

YOLOv4-tiny

The tiny and fast version of YOLOv4 - good for training and deployment on limited compute resources, and getting a feel for your dataset Read More...

YOLOv4-tiny Tutorial YOLOv4-tiny Repo YOLOv4-tiny Colab Notebook

Object Detection :: Darknet TXT

YOLOv4 Darknet

YOLOv4 has emerged as the best real time object detection model. YOLOv4 carries forward many of the research contributions of the YOLO family of models along with new modeling and data augmentation techniques. This implementation is in Darknet. Read More...

YOLOv4 Darknet Tutorial YOLOv4 Darknet Repo YOLOv4 Darknet Colab Notebook

PyTorch Object Detection :: YOLOv5 Oriented Bounding Boxes

YOLOv5-OBB

Oriented bounding boxes are bounding boxes rotated to better fit the objects represented on an angle. Read More...

YOLOv5-OBB Tutorial YOLOv5-OBB Video YOLOv5-OBB Repo YOLOv5-OBB Colab Notebook

PyTorch Object Detection :: COCO JSON

Detectron2

Detectron2 is a model zoo of it's own for computer vision models written in PyTorch. Detectron2 includes all the models that were available in the original Detectron, such as Faster R-CNN, Mask R-CNN, RetinaNet, and DensePose. It also features several new models, including Cascade R-CNN, Panoptic FPN, and TensorMask. Read More...

Detectron2 Tutorial Detectron2 Repo Detectron2 Colab Notebook

PyTorch Object Detection :: COCO JSON

EfficientDet

EfficientDet achieves the best performance in the fewest training epochs among object detection model architectures, making it a highly scalable architecture especially when operating with limited compute. Read More...

EfficientDet Tutorial EfficientDet Repo EfficientDet Jupyter Notebook EfficientDet Colab Notebook

Tensorflow 1.5 Object Detection :: TFRecord

Faster R-CNN

One of the most accurate object detection algorithms but requires a lot of power at inference time. A good choice if you can do processing asynchronously on a server. Read More...

Faster R-CNN Tutorial Faster R-CNN Repo Faster R-CNN Jupyter Notebook Faster R-CNN Colab Notebook

PyTorch Object Detection :: Darknet TXT

YOLO v3 PyTorch

Though it is no longer the most accurate object detection algorithm, YOLO v3 is still a very good choice when you need real-time detection while maintaining excellent accuracy. PyTorch version. Read More...

YOLO v3 PyTorch Video YOLO v3 PyTorch Repo YOLO v3 PyTorch Jupyter Notebook YOLO v3 PyTorch Colab Notebook

Keras Object Detection :: Keras TXT

YOLO v3 Keras

Though it is no longer the most accurate object detection algorithm, YOLO v3 is still a very good choice when you need real-time detection while maintaining excellent accuracy. Keras implementation. Read More...

YOLO v3 Keras Tutorial YOLO v3 Keras Repo YOLO v3 Keras Jupyter Notebook YOLO v3 Keras Colab Notebook

Tensorflow 1.5 Object Detection :: TFRecord

MobileNetSSDv2

This architecture provides good realtime results on limited compute. It's designed to run in realtime (30 frames per second) even on mobile devices. Read More...

MobileNetSSDv2 Tutorial MobileNetSSDv2 Repo MobileNetSSDv2 Jupyter Notebook MobileNetSSDv2 Colab Notebook

PyTorch Object Detection :: Darknet TXT

YOLOv4 PyTorch

YOLOv4 has emerged as one of the best real-time object detection models. YOLOv4 carries forward many of the research contributions of the YOLO family of models along with new modeling and data augmentation techniques. This implementation is in PyTorch. Read More...

YOLOv4 PyTorch Video YOLOv4 PyTorch Repo YOLOv4 PyTorch Colab Notebook