Introduction

Requirements

sudo apt-get install libsm6 libxext6 libxrender-dev libyaml-dev libpython3-dev

Tensorflow (2.x) & Tensorflow Addons (optional)

pip install tensorflow-gpu==2.4.0 --upgrade
pip install tensorflow-addons==0.12.0 --upgrade

Installation

pip install tf-semantic-segmentation

Features

• Fast and easy training/prediction on multiple datasets
• Distributed Training on Multiple GPUs
• Hyper Parameter Optimization using WandB
• WandB Integration
• Easily create TFRecord from Directory
• Tensorboard visualizations
• Ensemble inference

Datasets

• Ade20k
• Camvid
• Cityscapes
• MappingChallenge
• MotsChallenge
• Coco
• PascalVoc2012
• Taco
• Shapes (randomly creating triangles, rectangles and circles)
• Toy (Overlaying TinyImageNet with MNIST)
• ISIC2018
• CVC-ClinicDB

Models

• U2Net / U2NetP
• Unet
• PSP
• FCN
• Erfnet
• MultiResUnet
• NestedUnet (Unet++)
• SatelliteUnet
• MobilenetUnet (unet with mobilenet encoder pre-trained on imagenet)
• InceptionResnetV2Unet (unet with inception-resnet v2 encoder pre-trained on imagenet)
• ResnetUnet (unet with resnet50 encoder pre-trained on imagenet)
• AttentionUnet

Losses

• Catagorical Crossentropy
• Binary Crossentropy
• Crossentropy + SSIM
• Dice
• Crossentropy + Dice
• Tversky
• Focal
• Focal + Tversky

Metrics

• f1
• f2
• iou
• precision
• recall
• psnr
• ssim

Activations:

• mish
• swish
• relu6

Optimizers:

• Ranger
• RAdam

Normalization

• Instance Norm
• Batch Norm

Augmentations

• flip left/right
• flip up/down
• rot 180
• color