File size: 2,044 Bytes
af24ae8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 | """OCR engine abstraction with EasyOCR backend for Persian/English invoices."""
from __future__ import annotations
import logging
from io import BytesIO
from pathlib import Path
from typing import TYPE_CHECKING
import numpy as np
from PIL import Image
if TYPE_CHECKING:
from numpy.typing import NDArray
logger = logging.getLogger(__name__)
_reader = None
def _get_reader():
global _reader
if _reader is None:
import easyocr
logger.info("Initializing EasyOCR reader (fa + en)...")
_reader = easyocr.Reader(["fa", "en"], gpu=False, verbose=False)
return _reader
def load_image(source: str | Path | bytes | Image.Image) -> Image.Image:
if isinstance(source, Image.Image):
return source.convert("RGB")
if isinstance(source, bytes):
return Image.open(BytesIO(source)).convert("RGB")
path = Path(source)
if path.suffix.lower() == ".pdf":
from pdf2image import convert_from_path
pages = convert_from_path(str(path), dpi=200, first_page=1, last_page=1)
return pages[0].convert("RGB")
return Image.open(path).convert("RGB")
def image_to_array(image: Image.Image) -> "NDArray[np.uint8]":
return np.array(image)
def extract_text(image: Image.Image) -> tuple[str, list[dict]]:
"""Run OCR and return full text plus structured bounding-box results."""
reader = _get_reader()
arr = image_to_array(image)
results = reader.readtext(arr, detail=1, paragraph=False)
lines: list[str] = []
structured: list[dict] = []
for bbox, text, confidence in results:
cleaned = text.strip()
if not cleaned:
continue
lines.append(cleaned)
structured.append(
{
"text": cleaned,
"confidence": float(confidence),
"bbox": [[float(p[0]), float(p[1])] for p in bbox],
}
)
full_text = "\n".join(lines)
return full_text, structured
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