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.
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...
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...
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...
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...
PyTorch Object Detection :: COCO JSON
Detectron2
Detectron2 is 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...
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...
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...
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...
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...
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...
PyTorch Object Detection :: Darknet TXT
YOLOv4 PyTorch
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 PyTorch. Read More...