# Standard Modules import logging from pathlib import Path from PIL import Image # Internal Packages from src.utils.state import model from src.utils.constants import web_directory from src.search_type import image_search from src.utils.helpers import resolve_absolute_path from src.utils.rawconfig import ContentConfig, SearchConfig # Test # ---------------------------------------------------------------------------------------------------- def test_image_search_setup(content_config: ContentConfig, search_config: SearchConfig): # Act # Regenerate image search embeddings during image setup image_search_model = image_search.setup(content_config.image, search_config.image, regenerate=True) # Assert assert len(image_search_model.image_names) == 3 assert len(image_search_model.image_embeddings) == 3 # ---------------------------------------------------------------------------------------------------- def test_image_metadata(content_config: ContentConfig): "Verify XMP Description and Subjects Extracted from Image" # Arrange expected_metadata_image_name_pairs = [ (["Billi Ka Bacha.", "Cat", "Grass"], "kitten_park.jpg"), (["Pasture.", "Horse", "Dog"], "horse_dog.jpg"), (["Guinea Pig Eating Celery.", "Rodent", "Whiskers"], "guineapig_grass.jpg")] test_image_paths = [ Path(content_config.image.input_directories[0] / image_name[1]) for image_name in expected_metadata_image_name_pairs ] for expected_metadata, test_image_path in zip(expected_metadata_image_name_pairs, test_image_paths): # Act actual_metadata = image_search.extract_metadata(test_image_path) # Assert for expected_snippet in expected_metadata[0]: assert expected_snippet in actual_metadata # ---------------------------------------------------------------------------------------------------- def test_image_search(content_config: ContentConfig, search_config: SearchConfig): # Arrange output_directory = resolve_absolute_path(web_directory) model.image_search = image_search.setup(content_config.image, search_config.image, regenerate=False) query_expected_image_pairs = [("kitten", "kitten_park.jpg"), ("horse and dog in a farm", "horse_dog.jpg"), ("A guinea pig eating grass", "guineapig_grass.jpg")] # Act for query, expected_image_name in query_expected_image_pairs: hits = image_search.query( query, count = 1, model = model.image_search) results = image_search.collate_results( hits, model.image_search.image_names, output_directory=output_directory, image_files_url='/static/images', count=1) actual_image_path = output_directory.joinpath(Path(results[0].entry).name) actual_image = Image.open(actual_image_path) expected_image = Image.open(content_config.image.input_directories[0].joinpath(expected_image_name)) # Assert assert expected_image == actual_image # Cleanup # Delete the image files copied to results directory actual_image_path.unlink() # ---------------------------------------------------------------------------------------------------- def test_image_search_query_truncated(content_config: ContentConfig, search_config: SearchConfig, caplog): # Arrange model.image_search = image_search.setup(content_config.image, search_config.image, regenerate=False) max_words_supported = 10 query = " ".join(["hello"]*100) truncated_query = " ".join(["hello"]*max_words_supported) # Act try: with caplog.at_level(logging.INFO, logger="src.search_type.image_search"): image_search.query( query, count = 1, model = model.image_search) # Assert except RuntimeError as e: if "The size of tensor a (102) must match the size of tensor b (77)" in str(e): assert False, f"Query length exceeds max tokens supported by model\n" assert f"Find Images by Text: {truncated_query}" in caplog.text, "Query not truncated" # ---------------------------------------------------------------------------------------------------- def test_image_search_by_filepath(content_config: ContentConfig, search_config: SearchConfig, caplog): # Arrange output_directory = resolve_absolute_path(web_directory) model.image_search = image_search.setup(content_config.image, search_config.image, regenerate=False) image_directory = content_config.image.input_directories[0] query = f"file:{image_directory.joinpath('kitten_park.jpg')}" expected_image_path = f"{image_directory.joinpath('kitten_park.jpg')}" # Act with caplog.at_level(logging.INFO, logger="src.search_type.image_search"): hits = image_search.query( query, count = 1, model = model.image_search) results = image_search.collate_results( hits, model.image_search.image_names, output_directory=output_directory, image_files_url='/static/images', count=1) actual_image_path = output_directory.joinpath(Path(results[0].entry).name) actual_image = Image.open(actual_image_path) expected_image = Image.open(expected_image_path) # Assert # Ensure file search triggered instead of query with file path as string assert f"Find Images by Image: {resolve_absolute_path(expected_image_path)}" in caplog.text, "File search not triggered" # Ensure the correct image is returned assert expected_image == actual_image, "Incorrect image returned by file search" # Cleanup # Delete the image files copied to results directory actual_image_path.unlink()