Initial commit: Robot ökoszisztéma v2.0 - Stabilizált jármű és szerviz robotok
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38
backend/app/services/image_processor.py
Executable file
38
backend/app/services/image_processor.py
Executable file
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# /opt/docker/dev/service_finder/backend/app/services/image_processor.py
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import cv2
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import numpy as np
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from typing import Optional
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class DocumentImageProcessor:
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""" Saját képtisztító pipeline Robot 3 OCR számára. """
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@staticmethod
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def process_for_ocr(image_bytes: bytes) -> Optional[bytes]:
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if not image_bytes: return None
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try:
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nparr = np.frombuffer(image_bytes, np.uint8)
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img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
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if img is None: return None
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# 1. Előkészítés (Szürkeárnyalat + Felskálázás)
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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if gray.shape[1] < 1200:
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gray = cv2.resize(gray, None, fx=2.0, fy=2.0, interpolation=cv2.INTER_CUBIC)
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# 2. Kontraszt dúsítás (CLAHE)
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clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
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contrast = clahe.apply(gray)
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# 3. Adaptív Binarizálás (Fekete-fehér szöveg kiemelés)
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blur = cv2.GaussianBlur(contrast, (3, 3), 0)
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thresh = cv2.adaptiveThreshold(
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blur, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
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cv2.THRESH_BINARY, 11, 2
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)
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success, encoded_image = cv2.imencode('.png', thresh)
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return encoded_image.tobytes() if success else None
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except Exception as e:
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print(f"OpenCV Feldolgozási hiba: {e}")
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return None
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