SuryaOCR

vntocr_suryaocr.py

# Integrazione VNTranslator OCR con il motore SuryaOCR
# Versione: 1.0
# Autore: Fazx - GarudaMods | https://www.patreon.com/vntranslator

"""
# ==================================================================
# Surya OCR: https://github.com/VikParuchuri/surya
# Richiesto: python 3.10+ e PyTorch
# Installare con: pip install surya-ocr
# ==================================================================
# Eseguire questo script con: python vntocr_suryaocr.py
# In VNTranslator usa Custom Engine - HTTP POST con configurazione:
# -- URL: http://127.0.0.1:5353
# -- Tipo di contenuto: application/json
# -- Intestazioni: {}
# -- Corpo: {"image":"$IMAGE_BASE64", "langs": ["ja"]}
# -- Tipo di risposta: JSON
# -- Query di risposta: fullText
# ==================================================================
# Lingue (codice ISO a due lettere) https://en.wikipedia.org/wiki/List_of_ISO_639_language_codes
# -- Giapponese = ja
# -- Inglese = en
# ==================================================================
"""

from flask import Flask, request, jsonify
from PIL import Image
from io import BytesIO
import base64
import re
import json
from surya.ocr import run_ocr
from surya.model.detection.model import load_model as load_det_model, load_processor as load_det_processor
from surya.model.recognition.model import load_model as load_rec_model
from surya.model.recognition.processor import load_processor as load_rec_processor

APP_HOST = "localhost"
APP_PORT = 5353
APP_DEBUG = True

def format_ocr_result(ocr_result):
    full_text = ""
    boxes = []

    for result in ocr_result:
        for box in result["text_boxes"]:
            bbox = box["bbox"]
            x, y = bbox[0], bbox[1]
            w, h = bbox[2] - bbox[0], bbox[3] - bbox[1]
            boxes.append({
                "text": box["text"],
                "w": w,
                "h": h,
                "x": x,
                "y": y
            })

    boxes.sort(key=lambda box: (box["y"], box["x"]))
    full_text = " ".join(box["text"] for box in boxes).strip()

    return {
        "fullText": full_text,
        "boxes": boxes
    }

def parse_ocr_result(ocr_result):
    if not isinstance(ocr_result, list):
        raise ValueError("ocr_result is not a list")

    parsed_results = []
    for result in ocr_result:
        text_lines = []
        for line in result.text_lines:
            text_lines.append({
                "polygon": line.polygon,
                "confidence": line.confidence,
                "text": line.text,
                "bbox": line.bbox
            })

        parsed_results.append({
            "text_boxes": text_lines,
            "languages": result.languages,
            "image_bbox": result.image_bbox
        })

    return format_ocr_result(parsed_results)

############################################################

app = Flask(__name__)
det_processor = load_det_processor()
det_model = load_det_model()
rec_model = load_rec_model()
rec_processor = load_rec_processor()

@app.route("/", methods=["POST"])
def ocr_endpoint():    

    try:
        print("\n\n=== Richiesta OCR ===")
        print(f"Metodo: {request.method}")
        print(f"Intestazioni: {dict(request.headers)}")
        
        if not request.is_json:
            print("La richiesta non è JSON")
            return jsonify({"error": "La richiesta deve essere in formato JSON"}), 400
        
        data = request.get_json()

        # registra il payload
        print(f"Chiavi JSON della richiesta: {list(data.keys())}")

        # verifica immagine
        if "image" not in data:
            print("Nessun dato immagine")
            return jsonify({"error": "Nessun dato immagine"}), 400
        
        # decodifica immagine base64
        try:
            image_decode = base64.b64decode(data["image"])
            image = Image.open(BytesIO(image_decode))
            print("Immagine decodificata con successo da Base64")
        except Exception as e:
            print(f"Decodifica immagine fallita: {e}")
            return jsonify({"error": f"Decodifica immagine fallita: {str(e)}"}), 400

        # verifica langs
        langs = data.get("langs", ["ja"])
        print(f"langs: {langs}")

        # verifica disegno riquadro di delimitazione
        draw_bounding_box = data.get("draw_bounding_box", False)
        print(f"draw_bounding_box: {draw_bounding_box}")

        # esegui ocr
        # https://github.com/VikParuchuri/surya?tab=readme-ov-file#from-python
        result = run_ocr([image], [langs], det_model, det_processor, rec_model, rec_processor)
        print(f"OCR completato con successo: {result}")
        
        """
        [OCRResult(
            text_lines=[
                TextLine(polygon=[[0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0]], confidence=0.0, text='String', bbox=[0.0, 0.0, 0.0, 0.0]),
                TextLine(polygon=[[0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0]], confidence=0.0, text='String', bbox=[0.0, 0.0, 0.0, 0.0]),
                TextLine(polygon=[[0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0]], confidence=0.0, text='String', bbox=[0.0, 0.0, 0.0, 0.0])
            ], 
            languages=['ja'], image_bbox=[0.0, 0.0, 0.0, 0.0]
        )]
        """

        # analizza il risultato
        parsed_result = parse_ocr_result(result)       
        parsed_result['draw_bounding_box'] = draw_bounding_box
        json_result = json.dumps(parsed_result, indent=4, ensure_ascii=False)
        return json_result

    except Exception as e:
        print(f"Errore richiesta: {e}")
        return jsonify({"error": str(e)}), 500

if __name__ == "__main__":
    print(f"=== Avvio server OCR {APP_HOST} sulla porta {APP_PORT} ===")
    app.run(debug=APP_DEBUG, host=APP_HOST, port=APP_PORT)