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"""Tests for LinePredictor."""
import os
from pathlib import Path
import unittest
import editdistance
import numpy as np
from text_recognizer.datasets import IamLinesDataset
from text_recognizer.line_predictor import LinePredictor
import text_recognizer.util as util
SUPPORT_DIRNAME = Path(__file__).parents[0].resolve() / "support"
os.environ["CUDA_VISIBLE_DEVICES"] = ""
class TestEmnistLinePredictor(unittest.TestCase):
"""Test LinePredictor class on the EmnistLines dataset."""
def test_filename(self) -> None:
"""Test that LinePredictor correctly predicts on single images, for several test images."""
predictor = LinePredictor(
dataset="EmnistLineDataset", network_fn="CNNTransformer"
)
for filename in (SUPPORT_DIRNAME / "emnist_lines").glob("*.png"):
pred, conf = predictor.predict(str(filename))
true = str(filename.stem)
edit_distance = editdistance.eval(pred, true) / len(pred)
print(
f'Pred: "{pred}" | Confidence: {conf} | True: {true} | Edit distance: {edit_distance}'
)
self.assertLess(edit_distance, 0.2)
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