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MaskRCNN PyTorch checkpoint (FP32)

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Description

MaskRCNN PyTorch checkpoint trained with FP32

Publisher

NVIDIA Deep Learning Examples

Use Case

Segmentation

Framework

PyTorch

Latest Version

19.08.0

Modified

October 29, 2021

Size

337.99 MB

Model Overview

Mask R-CNN is a convolution based network for object instance segmentation. This implementation provides 1.3x faster training while maintaining target accuracy.

Model Architecture

Mask R-CNN builds on top of FasterRCNN adding an additional mask head for the task of image segmentation.

The architecture consists of following:

  • R-50 backbone with FPN
  • RPN head
  • RoI ALign
  • Bounding and classification box head
  • Mask head

Training

This model was trained using script available on NGC and in GitHub repo

Dataset

The following datasets were used to train this model:

  • COCO 2014 - Dataset for large-scale object detection, segmentation and captioning.

Performance

Performance numbers for this model are available in NGC

References

License

This model was trained using open-source software available in Deep Learning Examples repository. For terms of use, please refer to the license of the script and the datasets the model was derived from.