fix typos

README.md

@@ -18,12 +18,12 @@ we tested. Our pipeline can be applied to multi-view harmonization and stylizati
 Our implementation consists of:
 
 1. A python module used for training
-2. A plugin project on-top of [sIBR platform](https://sibr.gitlabpages.inria.fr/?page=index.html) that pre-processes the scene and  renders interactively the results of the training.
+2. A plugin project on top of [SIBR platform](https://sibr.gitlabpages.inria.fr/?page=index.html) that pre-processes the scene and renders interactively the results of the training.
 
 ## Recommended Setup
 
-* This is tested only in Windows 10 platform
-* A GPU with at least 12GB of memory for small scenes and 24GB for larger scenes, drivers, cuda 10.0 toolkit and cuDNN 7.5
+* This is tested only on Windows 10 platform
+* A GPU with at least 12GB of memory for small scenes and 24GB for larger scenes, drivers, Cuda 10.0 Toolkit, and cuDNN 7.5
 * Python 3.8 64-bit
 * Anaconda3 virtual environment
 * Cmake at least 3.18.0
@@ -32,9 +32,9 @@ Our implementation consists of:
 For preparing scenes from scratch:
 * [Colmap](https://colmap.github.io/) v3.6+
 
-## Compile sIBR
+## Compile SIBR
 
-This is a short step-by-step guide to compile sIBR with all the necessary projects. For the full sibr documentation please visit [here](https://sibr.gitlabpages.inria.fr/?page=index.html)
+This is a short step-by-step guide to compile SIBR with all the necessary projects. For the full SIBR documentation please visit [here](https://sibr.gitlabpages.inria.fr/?page=index.html)
 
 Compiling **with** scene preprocessing:
 ```.bash
@@ -71,7 +71,7 @@ cmake --build ./build --target INSTALL --config RelWithDebInfo
 
 ## Training a Scene
 
-### Prepare you own scene
+### Prepare your own scene
 
 Create your dataset directory PATH_TO_DATASET, and put your input images in PATH_TO_DATASET/images, then:
 
@@ -173,7 +173,7 @@ Prepare your Python environment run in a terminal:
 ```.bash
 conda create --prefix PATH_TO_YOUR_ENV python=3.8
 conda activate PATH_TO_YOUR_ENV
--- Follow instruction to install pytorch 1.9 from https://pytorch.org/get-started/locally/ --
+-- Follow the instructions to install pytorch 1.9 from https://pytorch.org/get-started/locally/ --
 conda install numpy tensorboard
 ```