| """EasyOCR-based text detector. Mirrors the current diagram_analysis.detect_text |
| behaviour (Reader(en, gpu=False), conf>=0.10) but without the legacy |
| _merge_nearby_texts post-processing so that comparison across OCR backends is |
| apples-to-apples on raw per-fragment detections.""" |
| from __future__ import annotations |
|
|
| import time |
| from typing import List |
|
|
| import cv2 |
| import easyocr |
| import numpy as np |
|
|
| _READER: easyocr.Reader | None = None |
|
|
|
|
| def _get_reader() -> easyocr.Reader: |
| global _READER |
| if _READER is None: |
| _READER = easyocr.Reader(["en"], gpu=False, verbose=False) |
| return _READER |
|
|
|
|
| def detect(image_path: str, min_conf: float = 0.10) -> dict: |
| img = cv2.imread(image_path) |
| if img is None: |
| raise FileNotFoundError(image_path) |
| reader = _get_reader() |
| start = time.perf_counter() |
| raw = reader.readtext(img) |
| elapsed = time.perf_counter() - start |
|
|
| texts: List[dict] = [] |
| for bbox, text, conf in raw: |
| if conf < min_conf: |
| continue |
| pts = np.array(bbox, dtype=np.int32) |
| x, y, w, h = cv2.boundingRect(pts) |
| texts.append( |
| { |
| "text": text.strip(), |
| "x": int(x), |
| "y": int(y), |
| "w": int(w), |
| "h": int(h), |
| "conf": float(conf), |
| } |
| ) |
| return {"texts": texts, "runtime_seconds": round(elapsed, 3)} |
|
|
