updated readme to fix directory and be more clear

README.md

@@ -47,12 +47,15 @@ git submodule update --init --recursive
 3. Set up environments:
 
 a. For material recognition/DBAT (uses conda):
+Get into Dynamic-Backward-Attention-Transformer directory,
 ```cmd
-cd Dynamic-Backward-Attention_Transformer
+cd Dynamic-Backward-Atention-Transformer
 conda env create -f environment.yml
 ```
 
+While inside DBAT folder,
 Download pre-trained [checkpoints](https://drive.google.com/file/d/1ov6ol7A4NU8chlT3oEwx-V51gbOU7GGD/view?usp=sharing) and also [swin_tiny_patch4_window7_224.pth](https://storage.openvinotoolkit.org/repositories/open_model_zoo/public/2022.1/swin-tiny-patch4-window7-224/?sort_by=NEW2OLD) into folder checkpoints
+Put epoch=126-valid_acc_epoch=0.87.ckpt checkpoint to Dynamic-Backward-Atention-Transformer\checkpoints\dpglt_mode95\accuracy and swin-tiny-patch4-window7-224.pth to Dynamic-Backward-Attention-Transformer\checkpoints\swin_pretrain
 ```cmd
 mkdir checkpoints\dpglt_mode95\accuracy checkpoints\swin_pretrain
 ```
@@ -68,6 +71,7 @@ c. For edgenet360 (uses WSL):
 - Make sure wsl thats called in cmd is the one with anaconda installed
 - Then create the tf2 environment:
 - MAKE SURE THE COMMAND BELOW ARE RUN IN WSL, from wsl, go up directory then go to /mnt/ to wherever the repo was in to access .yml
+
 ```cmd
 cd edgenet360
 conda env create -f tf2_new_env.yml
@@ -80,7 +84,6 @@ d. For 360monodepth (uses Docker):
 ```cmd
 cd 360monodepth
 docker build -t 360monodepth .
-docker run -it --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=0 360monodepth sh -c "cd /monodepth/code/python/src; python3 main.py --expname test_experiment --blending_method all --grid_size 8x7"
 ```
 
 4. Configure paths: