https://github.com/tonysy/drn-mxnet
Dense Relation Network: Learning Consistent and Context-Aware Representation For Semantic Image Segmentation. Modification of DRN source code
https://github.com/tonysy/drn-mxnet
artificial-intelligence computer-vision deep-learning semantic-segmentation
Last synced: 5 months ago
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Dense Relation Network: Learning Consistent and Context-Aware Representation For Semantic Image Segmentation. Modification of DRN source code
- Host: GitHub
- URL: https://github.com/tonysy/drn-mxnet
- Owner: tonysy
- Created: 2018-08-14T14:32:40.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2018-08-16T03:16:25.000Z (almost 7 years ago)
- Last Synced: 2025-01-06T03:00:32.902Z (5 months ago)
- Topics: artificial-intelligence, computer-vision, deep-learning, semantic-segmentation
- Language: Python
- Homepage:
- Size: 320 KB
- Stars: 25
- Watchers: 6
- Forks: 4
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
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README
# DRN-MXNet
The [author](https://github.com/zhuangyqin/DRN.git) of this projcet doesn't release the config file and usages.
I was working on semantic segmentation based on MXNet. So I have fix the errors and add usage for the original project.
## 1. Setup
- Python2.7
- OpenCV
- CUDA 8 or 9
### Build MXNet from Source:
- Clone the mxnet source code
- Put `ordering_op-inl.h` into `incubator-mxnet/src/operator/tensor`
- Put `softmax**` into `incubator-mxnet/src/operator/contrib`
- Follow the official instructions to build and install
- `sh init.sh` to build some libs for dataloader and detection task
### Get data and model
- Put data into `data/cistycapes`, you can use soft link to add the dataset
`ln -s ./data/cityscapes`
- Use the model provided by autho to load params(Optional)
- [Model](https://pan.baidu.com/s/14_zNi_m7hjv-sMWjY0D1Hw)
- It's not the pretrained model, so I just use it for test.
- I will try to generate a pretrained model recently
### Train with a simple config file
Because the original paper is not public now, I can only use some magic number of option to run this code. I am working on understanding the model from the code.
#### Train
`python2 experiment/deeplab/drn_train.py --cfg experiment/deeplab/cfgs/resnet_v2_38_deeplab_dcn_gru_v7.yaml`
#### Test
TBD
### Others
> main result on ade20k testing is 0.5635(symbol-v11)-single model main result on cityscapes testing is 82.4(symbol-v7) and 82.8(symbol-v13) - single model
> If you have question or some advice, email me '[email protected]'
> The model release on 'https://pan.baidu.com/s/14_zNi_m7hjv-sMWjY0D1Hw'
Thanks the author anyway!