Marmelator/image-classification-service
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This commit is contained in:
Matthias Bisping 2022-04-01 19:50:44 +02:00
parent c372529ee5
commit da9b3d0cb9
3 changed files with 17 additions and 13 deletions
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26
test/unit_tests/conftest.py
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@ -1,4 +1,5 @@
import random import random
import random
import string import string
import tempfile import tempfile
from functools import partial from functools import partial
@ -15,8 +16,12 @@ from image_prediction.classifier.classifier import Classifier
from image_prediction.classifier.image_classifier import ImageClassifier from image_prediction.classifier.image_classifier import ImageClassifier
from image_prediction.estimator.adapter.adapter import EstimatorAdapter from image_prediction.estimator.adapter.adapter import EstimatorAdapter
from image_prediction.estimator.preprocessor.preprocessors.basic import BasicPreprocessor from image_prediction.estimator.preprocessor.preprocessors.basic import BasicPreprocessor
from image_prediction.exceptions import UnknownEstimatorAdapter, UnknownImageExtractor, UnknownDatabaseType, \ from image_prediction.exceptions import (
UnknownLabelFormat UnknownEstimatorAdapter,
UnknownImageExtractor,
UnknownDatabaseType,
UnknownLabelFormat,
)
from image_prediction.image_extractor.extractor import ImageMetadataPair from image_prediction.image_extractor.extractor import ImageMetadataPair
from image_prediction.image_extractor.extractors.mock import ImageExtractorMock from image_prediction.image_extractor.extractors.mock import ImageExtractorMock
from image_prediction.image_extractor.extractors.parsable import ParsablePDFImageExtractor from image_prediction.image_extractor.extractors.parsable import ParsablePDFImageExtractor
@ -87,7 +92,7 @@ def label_format(request):
@pytest.fixture @pytest.fixture
def expected_predictions_mapped( def expected_predictions_mapped(
label_format, batch_of_expected_string_labels, batch_of_expected_label_to_probability_mappings label_format, batch_of_expected_string_labels, batch_of_expected_label_to_probability_mappings
): ):
if label_format == "index": if label_format == "index":
return batch_of_expected_string_labels return batch_of_expected_string_labels
@ -98,9 +103,7 @@ def expected_predictions_mapped(
@pytest.fixture @pytest.fixture
def expected_predictions( def expected_predictions(label_format, batch_of_expected_numeric_labels, batch_of_expected_probability_arrays):
label_format, batch_of_expected_numeric_labels, batch_of_expected_probability_arrays
):
if label_format == "index": if label_format == "index":
return batch_of_expected_numeric_labels return batch_of_expected_numeric_labels
elif label_format == "probability": elif label_format == "probability":
@ -111,7 +114,7 @@ def expected_predictions(
@pytest.fixture @pytest.fixture
def estimator_adapter( def estimator_adapter(
estimator_type, estimator_mock, keras_model, model_handle_mock, output_batch_generator, monkeypatch estimator_type, estimator_mock, keras_model, model_handle_mock, output_batch_generator, monkeypatch
): ):
if estimator_type == "mock": if estimator_type == "mock":
estimator_adapter = EstimatorAdapter(estimator_mock) estimator_adapter = EstimatorAdapter(estimator_mock)
@ -227,13 +230,14 @@ def map_labels(numeric_labels, classes):
@pytest.fixture @pytest.fixture
def metadata_plus_mapped_prediction(expected_predictions_mapped, metadata): def metadata_plus_mapped_prediction(expected_predictions_mapped, metadata):
return [{"classification": epm, **mdt} for epm, mdt in zip(expected_predictions_mapped, metadata)] return [{"classification": epm, **mdt} for epm, mdt in zip(expected_predictions_mapped, metadata)]
@pytest.fixture @pytest.fixture
def metadata_formatted_plus_mapped_prediction_formatted(expected_predictions_mapped_and_formatted, metadata_formatted): def metadata_formatted_plus_mapped_prediction_formatted(expected_predictions_mapped_and_formatted, metadata_formatted):
return [ return [
{"classification": epm, **mdt} for epm, mdt in zip(expected_predictions_mapped_and_formatted, metadata_formatted) {"classification": epm, **mdt}
for epm, mdt in zip(expected_predictions_mapped_and_formatted, metadata_formatted)
] ]
@ -330,7 +334,6 @@ def add_image_to_last_page(pdf: fpdf.fpdf.FPDF, image_metadata_pair):
@pytest.fixture @pytest.fixture
def model(): def model():
class Model: class Model:
@staticmethod @staticmethod
def predict(*args): def predict(*args):
return True return True
@ -377,12 +380,14 @@ def model_loader(database_connector):
@pytest.fixture @pytest.fixture
def mlflow_run_id(): def mlflow_run_id():
from image_prediction.config import CONFIG from image_prediction.config import CONFIG
return CONFIG.service.run_id return CONFIG.service.run_id
@pytest.fixture @pytest.fixture
def mlruns_dir(): def mlruns_dir():
from image_prediction.locations import MLRUNS_DIR from image_prediction.locations import MLRUNS_DIR
return MLRUNS_DIR return MLRUNS_DIR
@ -394,7 +399,6 @@ def mlflow_reader(mlruns_dir):
@pytest.fixture @pytest.fixture
def model_handle_mock(estimator_mock): def model_handle_mock(estimator_mock):
class ModelHandleMock: class ModelHandleMock:
def __init__(self): def __init__(self):
self.model = estimator_mock self.model = estimator_mock

2
test/unit_tests/label_mapper_test.py
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@ -13,7 +13,7 @@ def test_index_label_mapper(batch_of_expected_numeric_labels, batch_of_expected_
def test_array_label_mapper( def test_array_label_mapper(
batch_of_expected_probability_arrays, batch_of_expected_label_to_probability_mappings, classes batch_of_expected_probability_arrays, batch_of_expected_label_to_probability_mappings, classes
): ):
mapper = ProbabilityMapper(classes) mapper = ProbabilityMapper(classes)
assert list(mapper(batch_of_expected_probability_arrays)) == batch_of_expected_label_to_probability_mappings assert list(mapper(batch_of_expected_probability_arrays)) == batch_of_expected_label_to_probability_mappings

2
test/unit_tests/model_loader_test.py
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@ -18,4 +18,4 @@ def test_load_model_and_classes_from_mlflow_store(model_loader, mlflow_run_id):
classes_loaded = model_loader.load_classes(mlflow_run_id) classes_loaded = model_loader.load_classes(mlflow_run_id)
assert type(model_loaded) == PredictionModelHandle assert type(model_loaded) == PredictionModelHandle
assert classes_loaded == ['formula', 'logo', 'other', 'signature'] assert classes_loaded == ["formula", "logo", "other", "signature"]