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..	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation
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mask_rcnn	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN/mask_rcnn
scripts	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN/scripts
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Dockerfile	https://github.com/feifeibear/DeepLearningExamples/blob/master/TensorFlow2/Segmentation/MaskRCNN/Dockerfile
LICENSE	https://github.com/feifeibear/DeepLearningExamples/blob/master/TensorFlow2/Segmentation/MaskRCNN/LICENSE
LICENSE	https://github.com/feifeibear/DeepLearningExamples/blob/master/TensorFlow2/Segmentation/MaskRCNN/LICENSE
README.md	https://github.com/feifeibear/DeepLearningExamples/blob/master/TensorFlow2/Segmentation/MaskRCNN/README.md
README.md	https://github.com/feifeibear/DeepLearningExamples/blob/master/TensorFlow2/Segmentation/MaskRCNN/README.md
download_and_process_pretrained_weights.sh	https://github.com/feifeibear/DeepLearningExamples/blob/master/TensorFlow2/Segmentation/MaskRCNN/download_and_process_pretrained_weights.sh
download_and_process_pretrained_weights.sh	https://github.com/feifeibear/DeepLearningExamples/blob/master/TensorFlow2/Segmentation/MaskRCNN/download_and_process_pretrained_weights.sh
mask_rcnn_main.py	https://github.com/feifeibear/DeepLearningExamples/blob/master/TensorFlow2/Segmentation/MaskRCNN/mask_rcnn_main.py
mask_rcnn_main.py	https://github.com/feifeibear/DeepLearningExamples/blob/master/TensorFlow2/Segmentation/MaskRCNN/mask_rcnn_main.py
README.md	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#readme
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#mask-r-cnn-for-tensorflow
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#table-of-contents
Model overview	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#model-overview
Model architecture	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#model-architecture
Default configuration	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#default-configuration
Feature support matrix	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#feature-support-matrix
Features	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#features
Mixed precision training	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#mixed-precision-training
Enabling mixed precision	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#enabling-mixed-precision
Enabling TF32	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#enabling-tf32
Setup	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#setup
Requirements	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#requirements
Quick Start Guide	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#quick-start-guide
Advanced	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#advanced
Scripts and sample code	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#scripts-and-sample-code
Parameters	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#parameters
Command-line options	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#command-line-options
Getting the data	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#getting-the-data
Dataset guidelines	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#dataset-guidelines
Multi-dataset	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#multi-dataset
Training process	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-process
Inference process	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#inference-process
Performance	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#performance
Benchmarking	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#benchmarking
Training performance benchmark	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-performance-benchmark
Inference performance benchmark	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#inference-performance-benchmark
Results	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#results
Training accuracy results TensorFlow 1.1x	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-accuracy-results-tensorflow-11x
Training accuracy: NVIDIA DGX A100 (8x A100 40GB)	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-accuracy-nvidia-dgx-a100-8x-a100-40gb
Training accuracy: NVIDIA DGX-1 (8x V100 16GB)	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-accuracy-nvidia-dgx-1-8x-v100-16GB
Training performance results Tensorflow 1.1x	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-performance-results-tensorflow-11x
Training performance: NVIDIA DGX A100 (8x A100 40GB)	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-performance-nvidia-dgx-a100-8x-a100-40gb
Training performance: NVIDIA DGX-1 (8x V100 16GB)	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-performance-nvidia-dgx-1-8x-v100-16gb
Training accuracy results TensorFlow 2.x	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-accuracy-results-tensorflow-2x
Training accuracy: NVIDIA DGX A100 (8x A100 40GB)	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-accuracy-nvidia-dgx-a100-8x-a100-40gb-1
Training accuracy: NVIDIA DGX-1 (8x V100 16GB)	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-accuracy-nvidia-dgx-1-8x-v100-16gb-1
Training performance results Tensorflow 2.x	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-performance-results-tensorflow-2x
Training performance: NVIDIA DGX A100 (8x A100 40GB)	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-performance-nvidia-dgx-a100-8x-a100-40gb-1
Training performance: NVIDIA DGX-1 (8x V100 16GB)	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-performance-nvidia-dgx-1-8x-v100-16gb-1
Inference performance results TensorFlow 1.1x	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#inference-performance-results-tensorflow-11x
Inference performance: NVIDIA DGX A100 (1x A100 40GB)	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#inference-performance-nvidia-dgx-a100-1x-a100-40gb
Inference performance: NVIDIA DGX-1 (1x V100 16GB)	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#inference-performance-nvidia-dgx-1-1x-v100-16gb
Inference performance results TensorFlow 2.x	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#inference-performance-results-tensorflow-2x
Inference performance: NVIDIA DGX A100 (1x A100 40GB)	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#inference-performance-nvidia-dgx-a100-1x-a100-40gb-1
Inference performance: NVIDIA DGX-1 (1x V100 16GB)	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#inference-performance-nvidia-dgx-1-1x-v100-16gb-1
Release notes	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#release-notes
Changelog	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#changelog
Known issues	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#known-issues
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#model-overview
here	https://arxiv.org/abs/1703.06870
Google's TPU implementation	https://github.com/tensorflow/tpu/tree/master/models/official/mask_rcnn
TensorFlow AMP	https://docs.nvidia.com/deeplearning/frameworks/tensorflow-user-guide/index.html#tfamp
NVIDIA PyTorch implementation	https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Segmentation/MaskRCNN
Matterport	https://github.com/matterport/Mask_RCNN
Tensorpack	https://github.com/tensorpack/tensorpack/tree/master/examples/FasterRCNN
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#model-architecture
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#default-configuration
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#feature-support-matrix
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#features
Horovod: Official repository	https://github.com/horovod/horovod
TensorFlow tutorial	https://github.com/horovod/horovod/#usage
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#mixed-precision-training
Mixed precision	https://arxiv.org/abs/1710.03740
Tensor Cores	https://developer.nvidia.com/tensor-cores
mixed precision training	https://docs.nvidia.com/deeplearning/performance/mixed-precision-training/index.html
mixed precision methodology	https://docs.nvidia.com/deeplearning/sdk/mixed-precision-training/index.html#tensorflow
Mixed Precision Training	https://arxiv.org/abs/1710.03740
Training With Mixed Precision	https://docs.nvidia.com/deeplearning/performance/mixed-precision-training/index.html
Mixed-Precision Training of Deep Neural Networks	https://devblogs.nvidia.com/mixed-precision-training-deep-neural-networks/
Using TF-AMP	https://docs.nvidia.com/deeplearning/dgx/tensorflow-user-guide/index.html#tfamp
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#enabling-mixed-precision
loss scaling	https://docs.nvidia.com/deeplearning/sdk/mixed-precision-training/index.html#lossscaling
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#enabling-tf32
NVIDIA A100	https://www.nvidia.com/en-us/data-center/a100/
TensorFloat-32 in the A100 GPU Accelerates AI Training, HPC up to 20x	https://blogs.nvidia.com/blog/2020/05/14/tensorfloat-32-precision-format/
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#setup
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#requirements
NVIDIA Docker	https://github.com/NVIDIA/nvidia-docker
NGC container	https://ngc.nvidia.com/registry/nvidia-tensorflow
NVIDIA Volta	https://www.nvidia.com/en-us/data-center/volta-gpu-architecture/
NVIDIA Turing	https://www.nvidia.com/en-us/geforce/turing/
NVIDIA Ampere architecture	https://www.nvidia.com/en-us/data-center/nvidia-ampere-gpu-architecture/
Getting Started Using NVIDIA GPU Cloud	https://docs.nvidia.com/ngc/ngc-getting-started-guide/index.html
Accessing And Pulling From The NGC Container Registry	https://docs.nvidia.com/deeplearning/frameworks/user-guide/index.html#accessing_registry
TensorFlow	https://docs.nvidia.com/deeplearning/frameworks/tensorflow-release-notes/running.html#running
NVIDIA Container Support Matrix	https://docs.nvidia.com/deeplearning/frameworks/support-matrix/index.html
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#quick-start-guide
COCO 2017 dataset	http://cocodataset.org/#download
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#advanced
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#scripts-and-sample-code
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#parameters
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#mask_rcnn_mainpy-script-parameters
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#command-line-options
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#getting-the-data
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#dataset-guidelines
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-process
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#inference-process
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#performance
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#benchmarking
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-performance-benchmark
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#inference-performance-benchmark
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#results
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-accuracy-results-tensorflow-11x
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-accuracy-nvidia-dgx-a100-8x-a100-40gb
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-accuracy-nvidia-dgx-1-8x-v100-16gb
	https://github.com/feifeibear/DeepLearningExamples/blob/master/TensorFlow2/Segmentation/MaskRCNN/images/MaskRCNN_TF1_conv.png
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-performance-results-tensorflow-11x
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-performance-nvidia-dgx-a100-8x-a100-40gb
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-performance-nvidia-dgx-1-8x-v100-16gb
Quick Start Guide	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#quick-start-guide
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-accuracy-results-tensorflow-2x
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-accuracy-nvidia-dgx-a100-8x-a100-40gb-1
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-accuracy-nvidia-dgx-1-8x-v100-16gb-1
	https://github.com/feifeibear/DeepLearningExamples/blob/master/TensorFlow2/Segmentation/MaskRCNN/images/MaskRCNN_TF2_conv.png
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-performance-results-tensorflow-2x
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-performance-nvidia-dgx-a100-8x-a100-40gb-1
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#training-performance-nvidia-dgx-1-8x-v100-16gb-1
Quick Start Guide	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#quick-start-guide
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#inference-performance-results-tensorflow-11x
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#inference-performance-nvidia-dgx-a100-1x-a100-40gb
Quick Start Guide	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#quick-start-guide
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#inference-performance-nvidia-dgx-1-1x-v100-16gb
Quick Start Guide	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#quick-start-guide
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#inference-performance-results-tensorflow-2x
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#inference-performance-nvidia-dgx-a100-1x-a100-40gb-1
Quick Start Guide	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#quick-start-guide
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#inference-performance-nvidia-dgx-1-1x-v100-16gb-1
Quick Start Guide	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#quick-start-guide
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#release-notes
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#changelog
	https://github.com/feifeibear/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN#known-issues
	https://github.com
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