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  ![alt text](img/workflow.png)
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  ### Getting Started
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  ##### Recommend python 3.7, CUDA v11.3 and Pytorch 1.10.0.
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- ***Clone MMSegmentation***
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  ```bash
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- git clone https://github.com/open-mmlab/mmsegmentation.git -b v1.1.2
 
 
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  pip install -U openmim
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  mim install mmengine
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  β”œβ”€πŸ“ images/
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  β””β”€πŸ“ labelme_jsons/
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  </pre>
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- 2. Convert labelme files to mask:
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  ```bash
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  python run/labelme2mask.py
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  ```
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  β”œβ”€πŸ“ img_dir/
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  β””β”€πŸ“ ann_dir/
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  </pre>
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- 3. Split the training set and test set.
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  ```bash
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  python run/split_dataset.py
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  ```
 
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  ![alt text](img/workflow.png)
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  ### Getting Started
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  ##### Recommend python 3.7, CUDA v11.3 and Pytorch 1.10.0.
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+ ***Clone***
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  ```bash
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+ git clone https://huggingface.co/CVRPDataset/Model
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+ cd Model
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+ git clone https://github.com/open-mmlab/mmsegmentation.git -b v1.1.2 mmsegmentation
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  pip install -U openmim
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  mim install mmengine
 
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  β”œβ”€πŸ“ images/
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  β””β”€πŸ“ labelme_jsons/
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  </pre>
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+ 1. Convert labelme files to mask:
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  ```bash
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  python run/labelme2mask.py
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  ```
 
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  β”œβ”€πŸ“ img_dir/
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  β””β”€πŸ“ ann_dir/
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  </pre>
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+ 1. Split the training set and test set.
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  ```bash
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  python run/split_dataset.py
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  ```