diff --git a/README.md b/README.md
index 5028194..a51ce01 100644
--- a/README.md
+++ b/README.md
@@ -33,7 +33,7 @@ ISP pipeline for `InfiniteISP_ReferenceModel v1.0`
4. **Video Processing**: The model also features a video processing script that allows for sequential frame processing, with operational 3A Statistics data flowing between frames.
-
+5. **Support Multiple RAW formats**: The model supports supports renowned raw formats, for example, DNG (predominantly employed by Android devices), NEF (specific to Nikon devices), and CR2 (Canon's signature format). It can also process the .raw image format, a one-dimensional pixel data array with no metadata header.
## Objectives
@@ -104,14 +104,15 @@ RAW_DATA = './in_frames/normal/data'
## How to Run on Pipeline on Multiple Images/Dataset
-There are two scripts that run Infinite-ISP on multiple images:
+There is another script [isp_pipeline_multiple_images.py](isp_pipeline_multiple_images.py) that runs Infinite-ISP on multiple images with two modes:
-1. [isp_pipeline_dataset.py](isp_pipeline_dataset.py)
+1. DATASET PROCESSING
Execute multiple images. Raw image should have its own config file with name `-configs.yml` where `` is raw filename otherwise the default configuration file [configs.yml](config/configs.yml) is used.
+ For raw image format such as, NEF, DNG and CR2 we have also provided a funcationality to extract sensor information provided in these raw files metadata and update default config file.
-2. [video_processing.py](video_processing.py)
+2. VIDEO MODE
Each image in the dataset is considered as video frame in sequence. All images use the same configuration parameters from [configs.yml](config/configs.yml) and 3A Stats calculated on a frame are applied to the next frame.
After cloning the repository and installing all the dependencies follow the following steps:
@@ -125,7 +126,7 @@ DATASET_PATH = './in_frames/normal/data'
```shell
git submodule add
-git submodule update –-init –-recursive
+git submodule update --init --recursive
```