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6908b6eed3
This would previously return the infamous tensor size mismatch error Verify this error is not raised since adding the query truncation logic
142 lines
5.7 KiB
Python
142 lines
5.7 KiB
Python
# Standard Modules
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import logging
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from pathlib import Path
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from PIL import Image
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# Internal Packages
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from src.utils.state import model
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from src.utils.constants import web_directory
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from src.search_type import image_search
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from src.utils.helpers import resolve_absolute_path
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from src.utils.rawconfig import ContentConfig, SearchConfig
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# Test
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# ----------------------------------------------------------------------------------------------------
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def test_image_search_setup(content_config: ContentConfig, search_config: SearchConfig):
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# Act
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# Regenerate image search embeddings during image setup
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image_search_model = image_search.setup(content_config.image, search_config.image, regenerate=True)
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# Assert
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assert len(image_search_model.image_names) == 3
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assert len(image_search_model.image_embeddings) == 3
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# ----------------------------------------------------------------------------------------------------
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def test_image_metadata(content_config: ContentConfig):
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"Verify XMP Description and Subjects Extracted from Image"
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# Arrange
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expected_metadata_image_name_pairs = [
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(["Billi Ka Bacha.", "Cat", "Grass"], "kitten_park.jpg"),
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(["Pasture.", "Horse", "Dog"], "horse_dog.jpg"),
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(["Guinea Pig Eating Celery.", "Rodent", "Whiskers"], "guineapig_grass.jpg")]
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test_image_paths = [
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Path(content_config.image.input_directories[0] / image_name[1])
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for image_name in expected_metadata_image_name_pairs
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]
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for expected_metadata, test_image_path in zip(expected_metadata_image_name_pairs, test_image_paths):
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# Act
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actual_metadata = image_search.extract_metadata(test_image_path)
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# Assert
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for expected_snippet in expected_metadata[0]:
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assert expected_snippet in actual_metadata
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# ----------------------------------------------------------------------------------------------------
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def test_image_search(content_config: ContentConfig, search_config: SearchConfig):
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# Arrange
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output_directory = resolve_absolute_path(web_directory)
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model.image_search = image_search.setup(content_config.image, search_config.image, regenerate=False)
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query_expected_image_pairs = [("kitten", "kitten_park.jpg"),
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("horse and dog in a farm", "horse_dog.jpg"),
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("A guinea pig eating grass", "guineapig_grass.jpg")]
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# Act
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for query, expected_image_name in query_expected_image_pairs:
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hits = image_search.query(
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query,
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count = 1,
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model = model.image_search)
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results = image_search.collate_results(
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hits,
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model.image_search.image_names,
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output_directory=output_directory,
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image_files_url='/static/images',
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count=1)
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actual_image_path = output_directory.joinpath(Path(results[0].entry).name)
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actual_image = Image.open(actual_image_path)
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expected_image = Image.open(content_config.image.input_directories[0].joinpath(expected_image_name))
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# Assert
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assert expected_image == actual_image
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# Cleanup
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# Delete the image files copied to results directory
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actual_image_path.unlink()
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# ----------------------------------------------------------------------------------------------------
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def test_image_search_query_truncated(content_config: ContentConfig, search_config: SearchConfig, caplog):
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# Arrange
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model.image_search = image_search.setup(content_config.image, search_config.image, regenerate=False)
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max_words_supported = 10
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query = " ".join(["hello"]*100)
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truncated_query = " ".join(["hello"]*max_words_supported)
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# Act
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try:
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with caplog.at_level(logging.INFO, logger="src.search_type.image_search"):
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image_search.query(
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query,
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count = 1,
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model = model.image_search)
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# Assert
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except RuntimeError as e:
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if "The size of tensor a (102) must match the size of tensor b (77)" in str(e):
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assert False, f"Query length exceeds max tokens supported by model\n"
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assert f"Find Images by Text: {truncated_query}" in caplog.text, "Query not truncated"
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# ----------------------------------------------------------------------------------------------------
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def test_image_search_by_filepath(content_config: ContentConfig, search_config: SearchConfig, caplog):
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# Arrange
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output_directory = resolve_absolute_path(web_directory)
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model.image_search = image_search.setup(content_config.image, search_config.image, regenerate=False)
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image_directory = content_config.image.input_directories[0]
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query = f"file:{image_directory.joinpath('kitten_park.jpg')}"
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expected_image_path = f"{image_directory.joinpath('kitten_park.jpg')}"
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# Act
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with caplog.at_level(logging.INFO, logger="src.search_type.image_search"):
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hits = image_search.query(
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query,
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count = 1,
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model = model.image_search)
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results = image_search.collate_results(
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hits,
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model.image_search.image_names,
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output_directory=output_directory,
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image_files_url='/static/images',
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count=1)
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actual_image_path = output_directory.joinpath(Path(results[0].entry).name)
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actual_image = Image.open(actual_image_path)
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expected_image = Image.open(expected_image_path)
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# Assert
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# Ensure file search triggered instead of query with file path as string
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assert f"Find Images by Image: {resolve_absolute_path(expected_image_path)}" in caplog.text, "File search not triggered"
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# Ensure the correct image is returned
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assert expected_image == actual_image, "Incorrect image returned by file search"
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# Cleanup
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# Delete the image files copied to results directory
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actual_image_path.unlink()
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