Update README.md

README.md

@@ -25,6 +25,7 @@ cd mmsegmentation
 pip install -v -e .
 ```
 ***Creating a Dataset***
+Here is an example if you want to make own dataset.
 
 1. Directory structure of the dataset:
 <pre>
@@ -63,7 +64,7 @@ pip install -v -e .
 ***Dataset Configs***
 
 ```bash
-cd mmseg/datasets
+cd mmsegmentation/mmseg/datasets
 wget https://huggingface.co/CVRPDataset/Model/resolve/main/dataset_configs/CVRP.py
 wget https://huggingface.co/CVRPDataset/Model/resolve/main/dataset_configs/__init__.py
 cd ../../configs/_base_/datasets
@@ -109,17 +110,17 @@ You can generate model config files using *run_configs.py*
 
 ```bash
 mkdir 'work_dirs' 'CVRP_configs' 'outputs'
-python run/run_configs.py --model_name deeplabv3plus -m configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb4-160k_ade20k-512x512.py -d configs/_base_/datasets/CVRP_pipeline.py -c 2 -w work_dirs -s CVRP_configs
+python run/run_configs.py --model_name deeplabv3plus -m mmsegmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb4-160k_ade20k-512x512.py -d mmsegmentation/configs/_base_/datasets/CVRP_pipeline.py -c 2 -w mmsegmentation/work_dirs -s mmsegmentation/CVRP_configs
 
-python run/run_configs.py --model_name knet -m configs/knet/knet-s3_swin-l_upernet_8xb2-adamw-80k_ade20k-512x512.py -d configs/_base_/datasets/CVRP_pipeline.py -c 2 -w work_dirs -s CVRP_configs
+python run/run_configs.py --model_name knet -m mmsegmentation/configs/knet/knet-s3_swin-l_upernet_8xb2-adamw-80k_ade20k-512x512.py -d mmsegmentation/configs/_base_/datasets/CVRP_pipeline.py -c 2 -w mmsegmentation/work_dirs -s mmsegmentation/CVRP_configs
 
-python run/run_configs.py --model_name mask2former -m configs/mask2former/mask2former_swin-l-in22k-384x384-pre_8xb2-160k_ade20k-640x640.py -d configs/_base_/datasets/CVRP_pipeline.py -c 2 -w work_dirs -s CVRP_configs
+python run/run_configs.py --model_name mask2former -m mmsegmentation/configs/mask2former/mask2former_swin-l-in22k-384x384-pre_8xb2-160k_ade20k-640x640.py -d mmsegmentation/configs/_base_/datasets/CVRP_pipeline.py -c 2 -w mmsegmentation/work_dirs -s mmsegmentation/CVRP_configs
 
-python run/run_configs.py --model_name segformer -m configs/segformer/segformer_mit-b5_8xb2-160k_ade20k-512x512.py -d configs/_base_/datasets/CVRP_pipeline.py -c 2 -w work_dirs -s CVRP_configs
+python run/run_configs.py --model_name segformer -m mmsegmentation/configs/segformer/segformer_mit-b5_8xb2-160k_ade20k-512x512.py -d mmsegmentation/configs/_base_/datasets/CVRP_pipeline.py -c 2 -w mmsegmentation/work_dirs -s mmsegmentation/CVRP_configs
 ```
  Also, you can download model config files [here](https://huggingface.co/CVRPDataset/Model/tree/main/model_configs). 
- ```bash 
-cd CVRP_configs
+ ```bash
+cd mmsegmentation/CVRP_configs
 wget https://huggingface.co/CVRPDataset/Model/resolve/main/model_configs/CVRP_mask2former.py
  ```
 
@@ -133,7 +134,7 @@ Also, you can download checkpoint [here](https://huggingface.co/CVRPDataset/Mode
 ***Test***
 ```bash
 cd ..
-python run/test.py -d CVRPDataset/val -m CVRP_configs/CVRP_mask2former.py -pth work_dirs/CVRP_mask2former/Mask2Former.pth -o outputs/CVRP_mask2former
+python run/test.py -d mmsegmentation/CVRPDataset/val -m mmsegmentation/CVRP_configs/CVRP_mask2former.py -pth mmsegmentation/work_dirs/CVRP_mask2former/Mask2Former.pth -o mmsegmentation/outputs/CVRP_mask2former
 ```
 ### UI
 ##### We create a web user interface for annotation based on gradio: