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Fine Tuning Script For Layout Model Of Surya OCR.

This repository contains layout-fine-tune.ipynb file, Please use this file to fine tune Surya Layout Model. This model uses modified architecture of Segformer.

Setup Instructions

Clone the Surya OCR GitHub Repository

git clone https://github.com/vikp/surya.git
cd surya

Switch to v0.4.14

git checkout f7c6c04

Install Dependencies

You can install the required dependencies using the following command:

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.

from surya.input.processing import prepare_image_detection
from surya.model.detection.segformer import load_processor
from PIL import Image
image = Image.open("path/to/image")
images = [prepare_image_detection(img=image, processor=load_processor())]
import torch
images = torch.stack(images, dim=0).to(model.dtype).to(model.device)

Loading Model

from surya.model.detection.segformer import load_model
model = load_model("vikp/surya_layout2") 
output = model(pixel_values=images)

Note : Loss function

Surya-layout-Model does not have pre-defined loss function, We have to define it according to our dataset and the Requirements.

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