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README.md

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-license: mit
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+---
+license: mit
+---
+
+![alt text](https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcSksxbjFqxppkfVHAN30x6JjNc_3JGeGILZPA&s "Title")
+
+
+# Fine Tuning Script For Layout Model Of Surya OCR.
+
+This repository contains [layout-fine-tune.ipynb](https://huggingface.co/ketanmore/surya-layout-fine-tune-script/blob/main/layout-fine-tune.ipynb) file, Please use this file to fine tune [Surya Layout Model](https://huggingface.co/vikp/surya_layout2). This model uses modified architecture of Segformer.
+
+## Setup Instructions
+
+### Clone the Surya OCR GitHub Repository
+
+```bash
+git clone https://github.com/vikp/surya.git
+cd surya
+```
+
+### Switch to v0.4.14
+
+```bash
+git checkout f7c6c04
+```
+
+### Install Dependencies
+
+You can install the required dependencies using the following command:
+
+```bash
+pip install -r requirements.txt
+```
+
+# Image Pre-processing 
+
+For image pre-processing we can directly import a function and image processor from [surya ocr github repository](https://github.com/VikParuchuri/surya/tree/v0.4.14). 
+
+```python
+from surya.input.processing import prepare_image_detection
+```
+
+```python
+from surya.model.detection.segformer import load_processor
+```
+
+```python
+from PIL import Image
+image = Image.open("path/to/image)
+images = [prepare_image_detection(img=image, processor=load_processor())]
+```
+
+```python
+import torch
+images = torch.stack(images, dim=0).to(model.dtype).to(model.device)
+```
+
+# Loading Model
+
+```python
+from surya.model.detection.segformer import load_model
+```
+
+```python
+model = load_model("vikp/surya_layout2") 
+```
+
+```python
+output = model(pixel_values=images)
+```
+
+
+### Note : Loss function
+
+[Surya-layout-Model](https://huggingface.co/vikp/surya_layout2) does not have pre-defined loss function, We have to define it according to our dataset and the Requirements.