import gradio as gr
import spaces
from texify.inference import batch_inference
from texify.model.model import load_model
from texify.model.processor import load_processor
from PIL import Image

title="""# 🙋🏻‍♂️Welcome to🌟Tonic's👨🏻‍🔬Texify"""
description="""You can upload a picture with a math formula and this model will return latex formulas. Texify is a multimodal input model. You can use this Space to test out the current model [vikp/texify2](https://huggingface.co/vikp/texify2) You can also use  vikp/texify2🚀 by cloning this space.   Simply click here: [Duplicate Space](https://huggingface.co/spaces/Tonic1/texify?duplicate=true)
Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community 👻  [![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/GWpVpekp) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Tonic-AI](https://github.com/tonic-ai) & contribute to 🌟 [DataTonic](https://github.com/Tonic-AI/DataTonic) 🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗
"""

model = load_model()
processor = load_processor()

@spaces.GPU
def process_image(img):
#   img = Image.fromarray(img)
    
    results = batch_inference([img], model, processor)

    return '\n'.join(results) if isinstance(results, list) else results

with gr.Blocks() as app:
    gr.Markdown(title)
    gr.Markdown(description)
    with gr.Row():
        with gr.Column():
            image_input = gr.Image(type="pil")
        with gr.Column():
            output = gr.Textbox()
    image_input.change(process_image, inputs=image_input, outputs=output)

if __name__ == "__main__":
    app.launch()