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Mask R-CNN TensorFlow checkpoint (AMP)

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Description

Mask R-CNN TensorFlow checkpoint trained with AMP

Publisher

NVIDIA Deep Learning Examples

Use Case

Segmentation

Framework

TensorFlow

Latest Version

20.06.1

Modified

November 8, 2021

Size

780.49 MB

Model Overview

Mask R-CNN is a convolution based network for object instance segmentation.

Model Architecture

Mask R-CNN builds on top of Faster R-CNN adding a mask head for the task of image segmentation.

The architecture consists of the following:

  • ResNet-50 backbone with Feature Pyramid Network (FPN)
  • Region proposal network (RPN) head
  • RoI Align
  • Bounding and classification box head
  • Mask head

Architecture

Figure 1. Diagram of Mask R-CNN framework from original paper

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 2017 - 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.