feat: migrate VIN/receipt extractors and OCR service to engine abstraction (refs #117)
Replace direct pytesseract calls with OcrEngine interface in vin_extractor.py, receipt_extractor.py, and ocr_service.py. PSM mode fallbacks replaced with engine-agnostic single-line/single-word configs. Dead _process_ocr_data removed. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Eric Gullickson
@@ -1,5 +1,4 @@
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"""VIN-specific OCR extractor with preprocessing and validation."""
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import io
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import logging
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import os
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import time
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@@ -8,11 +7,10 @@ from datetime import datetime
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from typing import Optional
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import magic
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import pytesseract
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from PIL import Image
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from pillow_heif import register_heif_opener
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from app.config import settings
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from app.engines import OcrConfig, create_engine
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from app.extractors.base import BaseExtractor
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from app.preprocessors.vin_preprocessor import vin_preprocessor, BoundingBox
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from app.validators.vin_validator import vin_validator
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@@ -56,15 +54,15 @@ class VinExtractor(BaseExtractor):
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"image/heif",
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}
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# VIN character whitelist for Tesseract
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# VIN character whitelist (passed to engine for post-OCR filtering)
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VIN_WHITELIST = "ABCDEFGHJKLMNPRSTUVWXYZ0123456789"
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# Fixed debug output directory (inside container)
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DEBUG_DIR = "/tmp/vin-debug"
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def __init__(self) -> None:
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"""Initialize VIN extractor."""
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pytesseract.pytesseract.tesseract_cmd = settings.tesseract_cmd
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"""Initialize VIN extractor with engine from factory."""
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self._engine = create_engine()
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self._debug = settings.log_level.upper() == "DEBUG"
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def _save_debug_image(self, session_dir: str, name: str, data: bytes) -> None:
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@@ -135,21 +133,21 @@ class VinExtractor(BaseExtractor):
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# Perform OCR with VIN-optimized settings
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raw_text, word_confidences = self._perform_ocr(preprocessed_bytes)
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logger.debug("PSM 6 raw text: '%s'", raw_text)
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logger.debug("PSM 6 word confidences: %s", word_confidences)
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logger.debug("Primary OCR raw text: '%s'", raw_text)
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logger.debug("Primary OCR word confidences: %s", word_confidences)
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# Extract VIN candidates from raw text
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candidates = vin_validator.extract_candidates(raw_text)
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logger.debug("PSM 6 candidates: %s", candidates)
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logger.debug("Primary OCR candidates: %s", candidates)
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if not candidates:
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# No VIN candidates found - try with different PSM modes
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# No VIN candidates found - try alternate OCR configurations
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candidates = self._try_alternate_ocr(preprocessed_bytes)
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if not candidates:
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# Try grayscale-only (no thresholding) — the Tesseract
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# LSTM engine often performs better on non-binarized input
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# because it does its own internal preprocessing.
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# Try grayscale-only (no thresholding) — OCR engines often
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# perform better on non-binarized input because they do
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# their own internal preprocessing.
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gray_result = vin_preprocessor.preprocess(
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image_bytes, apply_threshold=False
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)
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@@ -166,9 +164,9 @@ class VinExtractor(BaseExtractor):
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raw_text, word_confidences = self._perform_ocr(
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gray_result.image_bytes
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)
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logger.debug("Gray PSM 6 raw text: '%s'", raw_text)
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logger.debug("Gray primary raw text: '%s'", raw_text)
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candidates = vin_validator.extract_candidates(raw_text)
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logger.debug("Gray PSM 6 candidates: %s", candidates)
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logger.debug("Gray primary candidates: %s", candidates)
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if not candidates:
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candidates = self._try_alternate_ocr(
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gray_result.image_bytes, prefix="Gray"
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@@ -188,9 +186,9 @@ class VinExtractor(BaseExtractor):
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)
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raw_text, word_confidences = self._perform_ocr(otsu_result.image_bytes)
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logger.debug("Otsu PSM 6 raw text: '%s'", raw_text)
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logger.debug("Otsu primary raw text: '%s'", raw_text)
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candidates = vin_validator.extract_candidates(raw_text)
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logger.debug("Otsu PSM 6 candidates: %s", candidates)
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logger.debug("Otsu primary candidates: %s", candidates)
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if not candidates:
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candidates = self._try_alternate_ocr(
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otsu_result.image_bytes, prefix="Otsu"
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@@ -280,52 +278,31 @@ class VinExtractor(BaseExtractor):
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return detected or "application/octet-stream"
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def _perform_ocr(
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self, image_bytes: bytes, psm: int = 6
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self,
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image_bytes: bytes,
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single_line: bool = False,
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single_word: bool = False,
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) -> tuple[str, list[float]]:
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"""
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Perform OCR with VIN-optimized settings.
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Perform OCR with VIN-optimized settings via engine abstraction.
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Args:
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image_bytes: Preprocessed image bytes
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psm: Tesseract page segmentation mode
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6 = Uniform block of text
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7 = Single text line
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8 = Single word
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single_line: Treat image as a single text line
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single_word: Treat image as a single word
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Returns:
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Tuple of (raw_text, word_confidences)
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"""
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image = Image.open(io.BytesIO(image_bytes))
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# Configure Tesseract for VIN extraction
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# OEM 1 = LSTM neural network engine (best accuracy)
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# NOTE: tessedit_char_whitelist does NOT work with OEM 1 (LSTM).
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# Using it causes empty/erratic output. Character filtering is
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# handled post-OCR by vin_validator.correct_ocr_errors() instead.
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config = (
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f"--psm {psm} "
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f"--oem 1 "
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f"-c load_system_dawg=false "
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f"-c load_freq_dawg=false"
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config = OcrConfig(
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char_whitelist=self.VIN_WHITELIST,
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single_line=single_line,
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single_word=single_word,
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use_angle_cls=True,
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)
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# Get detailed OCR data
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ocr_data = pytesseract.image_to_data(
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image, config=config, output_type=pytesseract.Output.DICT
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)
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# Extract words and confidences
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words = []
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confidences = []
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for i, text in enumerate(ocr_data["text"]):
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conf = int(ocr_data["conf"][i])
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if text.strip() and conf > 0:
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words.append(text.strip())
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confidences.append(conf / 100.0)
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raw_text = " ".join(words)
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return raw_text, confidences
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result = self._engine.recognize(image_bytes, config)
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word_confidences = [wb.confidence for wb in result.word_boxes]
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return result.text, word_confidences
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def _try_alternate_ocr(
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self,
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@@ -335,21 +312,25 @@ class VinExtractor(BaseExtractor):
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"""
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Try alternate OCR configurations when initial extraction fails.
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PSM modes tried in order:
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7 - Single text line
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8 - Single word
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11 - Sparse text (finds text in any order, good for angled photos)
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13 - Raw line (no Tesseract heuristics, good for clean VIN plates)
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Modes tried:
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single-line - Treat as a single text line
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single-word - Treat as a single word
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For PaddleOCR, angle classification handles rotated/angled text
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inherently, replacing the need for Tesseract PSM mode fallbacks.
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Returns:
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List of VIN candidates
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"""
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tag = f"{prefix} " if prefix else ""
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for psm in (7, 8, 11, 13):
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raw_text, _ = self._perform_ocr(image_bytes, psm=psm)
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logger.debug("%sPSM %d raw text: '%s'", tag, psm, raw_text)
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for mode_name, kwargs in [
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("single-line", {"single_line": True}),
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("single-word", {"single_word": True}),
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]:
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raw_text, _ = self._perform_ocr(image_bytes, **kwargs)
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logger.debug("%s%s raw text: '%s'", tag, mode_name, raw_text)
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candidates = vin_validator.extract_candidates(raw_text)
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logger.debug("%sPSM %d candidates: %s", tag, psm, candidates)
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logger.debug("%s%s candidates: %s", tag, mode_name, candidates)
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if candidates:
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return candidates
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