app-ocr.py

import base64
import io
import os
import shutil
import time
import uuid
from pathlib import Path

# import numpy as np
# import tempfile
# from PIL import Image
import gradio as gr
from modelscope import AutoModel, AutoTokenizer

UPLOAD_FOLDER = "./uploads"
RESULTS_FOLDER = "./results"


tokenizer = AutoTokenizer.from_pretrained("stepfun-ai/GOT-OCR2_0", trust_remote_code=True)
model = AutoModel.from_pretrained("stepfun-ai/GOT-OCR2_0", trust_remote_code=True, low_cpu_mem_usage=True, device_map="cuda", use_safetensors=True)
model = model.eval().cuda()

for folder in [UPLOAD_FOLDER, RESULTS_FOLDER]:
    if not os.path.exists(folder):
        os.makedirs(folder)


def image_to_base64(image):
    buffered = io.BytesIO()
    image.save(buffered, format="PNG")
    return base64.b64encode(buffered.getvalue()).decode()


def run_GOT(image, got_mode, fine_grained_mode="", ocr_color="", ocr_box=""):
    unique_id = str(uuid.uuid4())
    image_path = os.path.join(UPLOAD_FOLDER, f"{unique_id}.png")
    result_path = os.path.join(RESULTS_FOLDER, f"{unique_id}.html")

    shutil.copy(image, image_path)

    try:
        if got_mode == "plain texts OCR":
            res = model.chat(tokenizer, image_path, ocr_type="ocr")
            return res, None
        elif got_mode == "format texts OCR":
            res = model.chat(tokenizer, image_path, ocr_type="format", render=True, save_render_file=result_path)
        elif got_mode == "plain multi-crop OCR":
            res = model.chat_crop(tokenizer, image_path, ocr_type="ocr")
            return res, None
        elif got_mode == "format multi-crop OCR":
            res = model.chat_crop(tokenizer, image_path, ocr_type="format", render=True, save_render_file=result_path)
        elif got_mode == "plain fine-grained OCR":
            res = model.chat(tokenizer, image_path, ocr_type="ocr", ocr_box=ocr_box, ocr_color=ocr_color)
            return res, None
        elif got_mode == "format fine-grained OCR":
            res = model.chat(tokenizer, image_path, ocr_type="format", ocr_box=ocr_box, ocr_color=ocr_color, render=True, save_render_file=result_path)

        # res_markdown = f"$$ {res} $$"
        res_markdown = res

        if "format" in got_mode and os.path.exists(result_path):
            with open(result_path, "r") as f:
                html_content = f.read()
            encoded_html = base64.b64encode(html_content.encode("utf-8")).decode("utf-8")
            iframe_src = f"data:text/html;base64,{encoded_html}"
            iframe = f'<iframe src="{iframe_src}" width="100%" height="600px"></iframe>'
            download_link = f'<a href="data:text/html;base64,{encoded_html}" download="result_{unique_id}.html">Download Full Result</a>'
            return res_markdown, f"{download_link}<br>{iframe}"
        else:
            return res_markdown, None
    except Exception as e:
        return f"Error: {str(e)}", None
    finally:
        if os.path.exists(image_path):
            os.remove(image_path)


def task_update(task):
    if "fine-grained" in task:
        return [
            gr.update(visible=True),
            gr.update(visible=False),
            gr.update(visible=False),
        ]
    else:
        return [
            gr.update(visible=False),
            gr.update(visible=False),
            gr.update(visible=False),
        ]


def fine_grained_update(task):
    if task == "box":
        return [
            gr.update(visible=False, value=""),
            gr.update(visible=True),
        ]
    elif task == "color":
        return [
            gr.update(visible=True),
            gr.update(visible=False, value=""),
        ]


def cleanup_old_files():
    current_time = time.time()
    for folder in [UPLOAD_FOLDER, RESULTS_FOLDER]:
        for file_path in Path(folder).glob("*"):
            if current_time - file_path.stat().st_mtime > 3600:  # 1 hour
                file_path.unlink()


with gr.Blocks() as demo:
    with gr.Row():
        with gr.Column():
            image_input = gr.Image(type="filepath", label="上传图片")
            task_dropdown = gr.Dropdown(
                choices=[
                    "plain texts OCR",
                    "format texts OCR",
                    "plain multi-crop OCR",
                    "format multi-crop OCR",
                    "plain fine-grained OCR",
                    "format fine-grained OCR",
                ],
                label="选择GOT模式",
                value="plain texts OCR",
            )
            fine_grained_dropdown = gr.Dropdown(choices=["box", "color"], label="fine-grained type", visible=False)
            color_dropdown = gr.Dropdown(choices=["red", "green", "blue"], label="color list", visible=False)
            box_input = gr.Textbox(label="input box: [x1,y1,x2,y2]", placeholder="e.g., [0,0,100,100]", visible=False)
            submit_button = gr.Button("Submit")

        with gr.Column():
            ocr_result = gr.Textbox(label="GOT output")

    with gr.Column():
        gr.Markdown("**如果选择带格式的模式，mathpix结果将自动呈现如下:**")
        html_result = gr.HTML(label="rendered html", show_label=True)

    task_dropdown.change(task_update, inputs=[task_dropdown], outputs=[fine_grained_dropdown, color_dropdown, box_input])
    fine_grained_dropdown.change(fine_grained_update, inputs=[fine_grained_dropdown], outputs=[color_dropdown, box_input])

    submit_button.click(run_GOT, inputs=[image_input, task_dropdown, fine_grained_dropdown, color_dropdown, box_input], outputs=[ocr_result, html_result])

if __name__ == "__main__":
    cleanup_old_files()
    demo.launch()