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MaskRCNN TF2 checkpoint (AMP)

Logo for MaskRCNN TF2 checkpoint (AMP)
Description
MaskRCNN TensorFlow2 checkpoint trained with AMP
Publisher
NVIDIA Deep Learning Examples
Latest Version
21.02.0_amp
Modified
September 22, 2022
Size
338.39 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 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.