Update README.md

README.md

@@ -7,12 +7,9 @@ pipeline_tag: image-to-image
 tags:
 - medical
 ---
-This is Repo Consist of Model for synthetic data generation for the 2D CT-scans
-We build this models research purpose only.
+This repository contains a model specifically designed for synthetic data generation of 2D CT-scans, intended solely for research purposes. The base model we employed is Stable-Diffusion-Medium, which has been enhanced using ControlNet, a technique for exerting more precise control over the image generation process.
 
-We used Stable-Diffusion-Medium as a Base model and apply Controlnet on it, 
-
-For Pretraining we used Atlas Dataset From John Hopkins
+For pretraining, we utilized the Atlas Dataset from Johns Hopkins University. This dataset provided a comprehensive range of medical imaging data, crucial for the initial training phase of our model. Our aim with this project is to contribute to the medical imaging field by enabling more robust and versatile synthetic data generation.
 
 ```
 Training Details
@@ -25,7 +22,7 @@ Computes:
 
 Code for generation:
 
-```
+```python
 from diffusers import StableDiffusion3ControlNetPipeline, SD3ControlNetModel, UniPCMultistepScheduler, LDMSuperResolutionPipeline
 import torch
 from PIL import Image