Deep-Feature-Flow-Segmentation
Deep-Feature-Flow-Segmentation copied to clipboard
Deep Feature Flow for Video Semantic Segmentation
Deep Feature Flow for Video Semantic Segmentation
Based on Deeplab V2
1. Setup environment
- If you use our dockerfile, you can run the code easily.
- If you want to set up your own env, please follow these steps:
- We only support
python2.7
now - Install tk:
sudo apt-get -y install python-tk
- Install OpenCV 3.4.1
- Install needed python packages with
pip install -r requirements.txt
- If you are in China Mainland, you can use these to speedup
pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
- If you are in China Mainland, you can use these to speedup
- We only support
- Then
sh init.sh
to build the lib for faster-rcnn Because we use the code from Deformable ConvNets and the dataloader has some dependencies on faster-rcnn, so you need to build the lib first.
2. Prepare Data and Pretrained Model
Cityscapes Data
You need to download the cityscapes data from the official webpapge and unzip the data
Put the data into data/cityscapes
, you can use soft link to set the data path as the following:
ln -s Dataset_path ./data/cityscapes
If you want to try DFF, you should download cityscapes video data and put it into data/cityscapes_video
Pretrained Model
Download pretrained resnet model flow net from Onedrive, and put the model into mode/pretrained_model/
./model/pretrained_model/resnet_v1_101-0000.params
./model/pretrained_model/flownet-0000.params
3. Train and Test
Training Deeplab V2
python ./experiments/deeplab/deeplab_train_test.py --cfg ./experiments/deeplab/cfgs/deeplab_resnet_v1_101_cityscapes_segmentation_base.yaml
Training Deeplab V2 Deformable
python ./experiments/deeplab/deeplab_train_test.py --cfg ./experiments/deeplab/cfgs/deeplab_resnet_v1_101_cityscapes_segmentation_dcn.yaml
Training DFF Deeplab V2
python ./experiments/deeplab_dff/deeplab_dff_train.py --cfg ./experiments/deeplab_dff/cfgs/deeplab_resnet_v1_101_cityscapes_segmentation_video.yaml
4. Performance
TBD
5. TODO List
- [x] Add Scripts
- [ ] Add experiment results
- [ ] Add support for Deeplab V3+
- [ ] Add BiSeNet
6. FAQ
- Program hang if your system opencv is 2.x and your opencv-python is 3.x
7. Acknowledgement
Thanks for the official deep featuere flow implementation and deeplab implementation from MSRACVER