app.py

import os
import streamlit as st
from transformers import AutoModel, AutoTokenizer
from PIL import Image
import base64
import uuid
import time
from pathlib import Path

# Force the use of CPU
os.environ["CUDA_VISIBLE_DEVICES"] = "-1"

# Load tokenizer and model on CPU
tokenizer = AutoTokenizer.from_pretrained('srimanth-d/GOT_CPU', trust_remote_code=True)
model = AutoModel.from_pretrained('srimanth-d/GOT_CPU', trust_remote_code=True, use_safetensors=True, pad_token_id=tokenizer.eos_token_id)
model.eval()

# Define folders for uploads and results
UPLOAD_FOLDER = "./uploads"
RESULTS_FOLDER = "./results"

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

# Function to run the GOT model
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")
    
    image.save(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 = 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>'
            return res_markdown, 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)

# Function to clean up old files
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()

# Streamlit App
st.set_page_config(page_title="GOT-OCR-2.0 Demo", layout="wide")

uploaded_image = st.file_uploader("Upload your image", type=["png", "jpg", "jpeg"])

# Create two columns for layout
col1, col2 = st.columns(2)

if uploaded_image:
    image = Image.open(uploaded_image)
    
    with col1:
        st.image(image, caption='Uploaded Image', use_column_width=True)

    with col2:
        got_mode = st.selectbox("Choose one mode of GOT", [
            "plain texts OCR",
            "format texts OCR",
            "plain multi-crop OCR",
            "format multi-crop OCR",
            "plain fine-grained OCR",
            "format fine-grained OCR",
        ])

        fine_grained_mode = None
        ocr_color = ""
        ocr_box = ""

        if "fine-grained" in got_mode:
            fine_grained_mode = st.selectbox("Fine-grained type", ["box", "color"])
            if fine_grained_mode == "box":
                ocr_box = st.text_input("Input box: [x1,y1,x2,y2]", value="[0,0,100,100]")
            elif fine_grained_mode == "color":
                ocr_color = st.selectbox("Color list", ["red", "green", "blue"])

        if st.button("Submit"):
            with st.spinner("Processing..."):
                result_text, html_result = run_GOT(image, got_mode, fine_grained_mode, ocr_color, ocr_box)
                st.text_area("GOT Output", result_text, height=200)

                if html_result:
                    st.markdown(html_result, unsafe_allow_html=True)

# Cleanup old files
cleanup_old_files()