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7b0cda0 | 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 | import numpy as np
import pytest
from unittest.mock import patch
from src.ocr_utils import ocr_title, ocr_sensors
@patch("src.ocr_utils.pytesseract.image_to_string")
def test_ocr_title_basic(mock_tesseract):
# Подделываем OCR-результат
mock_tesseract.return_value = "TEST_TITLE"
# Синтетическое изображение
img = np.zeros((50, 200, 3), dtype=np.uint8)
text = ocr_title(img)
assert text == "TEST_TITLE"
mock_tesseract.assert_called_once()
@patch("src.ocr_utils.paddle_ocr.predict")
def test_ocr_sensors_basic(mock_predict):
# Подменяем результат работы paddleocr.predict
mock_predict.return_value = [
{"rec_texts": ["123"], "rec_scores": [0.98]}
]
# Одна синтетическая ROI
img = np.zeros((20, 60, 3), dtype=np.uint8)
out = ocr_sensors([img])
assert isinstance(out, list)
assert len(out) == 1
assert out[0]["text"] == "123"
assert out[0]["score"] == 0.98
mock_predict.assert_called_once()
@patch("src.ocr_utils.paddle_ocr.predict")
def test_ocr_sensors_empty_roi(mock_predict):
# paddleOCR должен корректно отработать
mock_predict.return_value = [
{"rec_texts": [""], "rec_scores": [0]}
]
img = np.zeros((10, 10, 3), dtype=np.uint8)
out = ocr_sensors([img])
assert out[0]["text"] == ""
assert out[0]["score"] == 0
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