Back to Models

TensorFlow 2 Detection Model Zoo

research/object_detection/g3doc/tf2_detection_zoo.md

2.20.010.3 KB
Original Source

TensorFlow 2 Detection Model Zoo

<!-- mdlint off(URL_BAD_G3DOC_PATH) -->

We provide a collection of detection models pre-trained on the COCO 2017 dataset. These models can be useful for out-of-the-box inference if you are interested in categories already in those datasets. You can try it in our inference colab

They are also useful for initializing your models when training on novel datasets. You can try this out on our few-shot training colab.

Please look at this guide for mobile inference.

<!-- mdlint on -->

Finally, if you would like to train these models from scratch, you can find the model configs in this directory (also in the linked tar.gzs).

Model nameSpeed (ms)COCO mAPOutputs
CenterNet HourGlass104 512x5127041.9Boxes
CenterNet HourGlass104 Keypoints 512x5127640.0/61.4Boxes/Keypoints
CenterNet HourGlass104 1024x102419744.5Boxes
CenterNet HourGlass104 Keypoints 1024x102421142.8/64.5Boxes/Keypoints
CenterNet Resnet50 V1 FPN 512x5122731.2Boxes
CenterNet Resnet50 V1 FPN Keypoints 512x5123029.3/50.7Boxes/Keypoints
CenterNet Resnet101 V1 FPN 512x5123434.2Boxes
CenterNet Resnet50 V2 512x5122729.5Boxes
CenterNet Resnet50 V2 Keypoints 512x5123027.6/48.2Boxes/Keypoints
CenterNet MobileNetV2 FPN 512x512623.4Boxes
CenterNet MobileNetV2 FPN Keypoints 512x512641.7Keypoints
EfficientDet D0 512x5123933.6Boxes
EfficientDet D1 640x6405438.4Boxes
EfficientDet D2 768x7686741.8Boxes
EfficientDet D3 896x8969545.4Boxes
EfficientDet D4 1024x102413348.5Boxes
EfficientDet D5 1280x128022249.7Boxes
EfficientDet D6 1280x128026850.5Boxes
EfficientDet D7 1536x153632551.2Boxes
SSD MobileNet v2 320x3201920.2Boxes
SSD MobileNet V1 FPN 640x6404829.1Boxes
SSD MobileNet V2 FPNLite 320x3202222.2Boxes
SSD MobileNet V2 FPNLite 640x6403928.2Boxes
SSD ResNet50 V1 FPN 640x640 (RetinaNet50)4634.3Boxes
SSD ResNet50 V1 FPN 1024x1024 (RetinaNet50)8738.3Boxes
SSD ResNet101 V1 FPN 640x640 (RetinaNet101)5735.6Boxes
SSD ResNet101 V1 FPN 1024x1024 (RetinaNet101)10439.5Boxes
SSD ResNet152 V1 FPN 640x640 (RetinaNet152)8035.4Boxes
SSD ResNet152 V1 FPN 1024x1024 (RetinaNet152)11139.6Boxes
Faster R-CNN ResNet50 V1 640x6405329.3Boxes
Faster R-CNN ResNet50 V1 1024x10246531.0Boxes
Faster R-CNN ResNet50 V1 800x13336531.6Boxes
Faster R-CNN ResNet101 V1 640x6405531.8Boxes
Faster R-CNN ResNet101 V1 1024x10247237.1Boxes
Faster R-CNN ResNet101 V1 800x13337736.6Boxes
Faster R-CNN ResNet152 V1 640x6406432.4Boxes
Faster R-CNN ResNet152 V1 1024x10248537.6Boxes
Faster R-CNN ResNet152 V1 800x133310137.4Boxes
Faster R-CNN Inception ResNet V2 640x64020637.7Boxes
Faster R-CNN Inception ResNet V2 1024x102423638.7Boxes
Mask R-CNN Inception ResNet V2 1024x102430139.0/34.6Boxes/Masks
ExtremeNet (deprecated)----Boxes
ExtremeNet----Boxes