This repository contains the data and code for "Trans2Seg: Transparent Object Segmentation with Transformer ".

• python 3
• torch = 1.4.0
• torchvision
• pyyaml
• Pillow
• numpy

python setup.py develop --user

1. create dirs './datasets/transparent/Trans10K_v2'
2. put the train/validation/test data under './datasets/transparent/Trans10K_v2'. Data Structure is shown below.

Trans10K_v2
├── test
│   ├── images
│   └── masks_12
├── train
│   ├── images
│   └── masks_12
└── validation
    ├── images
    └── masks_12

Dataset will be released soon.

The code of Network pipeline is in segmentron/models/trans2seg.py.

The code of Transformer Encoder-Decoder is in segmentron/modules/transformer.py.

Our experiments are based on one machine with 8 V100 GPUs with 32g memory, about 1 hour training time.

bash tools/dist_train.sh $CONFIG-FILE $GPUS

For example:

bash tools/dist_train.sh configs/trans10kv2/trans2seg/trans2seg_medium.yaml 8

bash tools/dist_train.sh $CONFIG-FILE $GPUS --test TEST.TEST_MODEL_PATH $MODEL_PATH