MaskRCNN TensorFlow2 checkpoint trained with AMP
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
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.