metadata
license: mit
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.