app.py

import os
import PIL
import gradio as gr
from PIL import Image

os.system("pip install pix2tex")
os.system("pip install opencv-python-headless==4.1.2.30")

# Load model
from pix2tex import cli as pix2tex

model = pix2tex.LatexOCR()


def inference(input_image_path):
    img = Image.open(input_image_path)
    output = model(img)
    print("Model output:",output)
    return output


# Front end
title = "Convert images of equations into LaTeX code 📚✖️➕ 🔢"
description = "<div> Did you come across a complex mathematical expression that you want to refer to in your report/thesis? Is your freemium over at <a href='https://mathpix.com/' target='_blank'>Mathpix</a>? 😫 <br><br> Take a screenshot of the equation and use this application to convert it into LaTeX code. 😎  To use it, simply upload your screenshot/equation image, or click one of the examples to load them. To verify the results, copy & paste the output in <a href='https://quicklatex.com/' target='_blank'>Quick LaTeX</a>. Read more at the links below.</div>"
article = "<p style='text-align: center'><a href='https://lukas-blecher.github.io/LaTeX-OCR/' target='_blank'>pix2tex: Using a ViT to convert images of equations into LaTeX code</a> | <a href='https://github.com/lukas-blecher/LaTeX-OCR' target='_blank'>Github</a></p>"


# UI
gr.Interface(
    inference,
    title=title,
    description=description,
    article=article,
    inputs=gr.inputs.Image(type="filepath", label="Input: Image of your equation you want to covert."),
    outputs=gr.outputs.Textbox(type="text", label="Output: Converted LaTeX code."),
    examples=["./eqn1.png", "./eqn2.png", "./eqn3.png"],
    allow_flagging="never",
    analytics_enabled=False,
).launch()