Mask R-CNN is a convolution based network for object instance segmentation. This implementation provides 1.3x faster training while maintaining target accuracy.
The following section lists the requirements that you need to meet in order to start training the Mask R-CNN model.
Requirements
This repository contains Dockerfile which extends the TensorFlow 2 NGC container and encapsulates some dependencies. Aside from these dependencies, ensure you have the following components:
- NVIDIA Docker
- TensorFlow 21.02 NGC container
- Supported GPUs:
- NVIDIA Volta architecture
- NVIDIA Turing architecture
- NVIDIA Ampere architecture
For more information about how to get started with NGC containers, see the following sections from the NVIDIA GPU Cloud Documentation and the Deep Learning Documentation:
- Getting Started Using NVIDIA GPU Cloud
- Accessing And Pulling From The NGC Container Registry
- Running [framework name - link to topic]
For those unable to use the TensorFlow 2 NGC container, to set up the required environment or create your own container, see the versioned NVIDIA Container Support Matrix.