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Fast Video Object Segmentation by Reference-Guided Mask Propagation

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Name		Name	Last commit message	Last commit date
Latest commit History 20 Commits
results		results
README.md		README.md
model.py		model.py
run.py		run.py
train.py		train.py
utils.py		utils.py
val.py		val.py

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RGMP PyTorch

This is forked from the official demo code for the paper. PDF

Added training script with TensorBoard support.

Test Environment

Ubuntu
python 3.6
Pytorch 0.3.1
- installed with CUDA.

How to Run Inference

Download DAVIS-2017.
Edit path for DAVIS_ROOT in run.py.

DAVIS_ROOT = '<Your DAVIS path>'

Download weights.pth and place it the same folde as run.py.
To run single-object video object segmentation on DAVIS-2016 validation.

python run.py

To run multi-object video object segmentation on DAVIS-2017 validation.

python run.py -MO

Results will be saved in ./results/SO or ./results/MO.

How to train a model

python3 train.py

TensorBoard Support

Install TensorBoardX to view loss, IoU and generated masks in real-time during training.

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Fast Video Object Segmentation by Reference-Guided Mask Propagation

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