haofengac / RGMP

Fast Video Object Segmentation by Reference-Guided Mask Propagation

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

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

DAVIS_ROOT = '<Your DAVIS path>'

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

python run.py

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

python run.py -MO

6. 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.