diff options
author | Gustaf Rydholm <gustaf.rydholm@gmail.com> | 2022-02-06 22:42:42 +0100 |
---|---|---|
committer | Gustaf Rydholm <gustaf.rydholm@gmail.com> | 2022-02-06 22:42:42 +0100 |
commit | 2d4e527fc0d47db8ed995180cbcec01271e20245 (patch) | |
tree | b3d8266191632df5c0668bb6eb56bc5cdc2def90 /tests | |
parent | 1e09d9d340fd214ee48fb093d51c67a415b3be19 (diff) |
chore: remove tests
Diffstat (limited to 'tests')
-rw-r--r-- | tests/test_character_predictor.py | 31 | ||||
-rw-r--r-- | tests/test_line_predictor.py | 35 | ||||
-rw-r--r-- | tests/test_paragraph_text_recognizer.py | 37 |
3 files changed, 0 insertions, 103 deletions
diff --git a/tests/test_character_predictor.py b/tests/test_character_predictor.py deleted file mode 100644 index 01bda78..0000000 --- a/tests/test_character_predictor.py +++ /dev/null @@ -1,31 +0,0 @@ -"""Test for CharacterPredictor class.""" -import importlib -import os -from pathlib import Path -import unittest - -from loguru import logger - -from text_recognizer.character_predictor import CharacterPredictor -from text_recognizer.networks import MLP - -SUPPORT_DIRNAME = Path(__file__).parents[0].resolve() / "support" / "emnist" - -os.environ["CUDA_VISIBLE_DEVICES"] = "" - - -class TestCharacterPredictor(unittest.TestCase): - """Tests for the CharacterPredictor class.""" - - def test_filename(self) -> None: - """Test that CharacterPredictor correctly predicts on a single image, for serveral test images.""" - network_fn_ = MLP - predictor = CharacterPredictor(network_fn=network_fn_) - - for filename in SUPPORT_DIRNAME.glob("*.png"): - pred, conf = predictor.predict(str(filename)) - logger.info( - f"Prediction: {pred} at confidence: {conf} for image with character {filename.stem}" - ) - self.assertEqual(pred, filename.stem) - self.assertGreater(conf, 0.7) diff --git a/tests/test_line_predictor.py b/tests/test_line_predictor.py deleted file mode 100644 index eede4d4..0000000 --- a/tests/test_line_predictor.py +++ /dev/null @@ -1,35 +0,0 @@ -"""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) diff --git a/tests/test_paragraph_text_recognizer.py b/tests/test_paragraph_text_recognizer.py deleted file mode 100644 index 3e280b9..0000000 --- a/tests/test_paragraph_text_recognizer.py +++ /dev/null @@ -1,37 +0,0 @@ -"""Test for ParagraphTextRecognizer class.""" -import os -from pathlib import Path -import unittest - -from text_recognizer.paragraph_text_recognizer import ParagraphTextRecognizor -import text_recognizer.util as util - - -SUPPORT_DIRNAME = Path(__file__).parents[0].resolve() / "support" / "iam_paragraph" - -# Prevent using GPU. -os.environ["CUDA_VISIBLE_DEVICES"] = "" - - -class TestParagraphTextRecognizor(unittest.TestCase): - """Test that it can take non-square images of max dimension larger than 256px.""" - - def test_filename(self) -> None: - """Test model on support image.""" - line_predictor_args = { - "dataset": "EmnistLineDataset", - "network_fn": "CNNTransformer", - } - line_detector_args = {"dataset": "EmnistLineDataset", "network_fn": "UNet"} - model = ParagraphTextRecognizor( - line_predictor_args=line_predictor_args, - line_detector_args=line_detector_args, - ) - num_text_lines_by_name = {"a01-000u-cropped": 7} - for filename in (SUPPORT_DIRNAME).glob("*.jpg"): - full_image = util.read_image(str(filename), grayscale=True) - predicted_text, line_region_crops = model.predict(full_image) - print(predicted_text) - self.assertTrue( - len(line_region_crops), num_text_lines_by_name[filename.stem] - ) |