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123 строки
4.6 KiB
Python
123 строки
4.6 KiB
Python
from ammico.image_summary import ImageSummaryDetector
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import os
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from PIL import Image
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import pytest
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@pytest.mark.long
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def test_image_summary_detector(model, get_testdict):
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detector = ImageSummaryDetector(summary_model=model, subdict=get_testdict)
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results = detector.analyse_images_from_dict(analysis_type="summary")
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assert len(results) == 2
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for key in get_testdict.keys():
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assert key in results
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assert "caption" in results[key]
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assert isinstance(results[key]["caption"], str)
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assert len(results[key]["caption"]) > 0
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@pytest.mark.long
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def test_image_summary_detector_questions(model, get_testdict):
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list_of_questions = [
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"What is happening in the image?",
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"How many cars are in the image in total?",
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]
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detector = ImageSummaryDetector(summary_model=model, subdict=get_testdict)
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results = detector.analyse_images_from_dict(
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analysis_type="questions", list_of_questions=list_of_questions
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)
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assert len(results) == 2
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for key in get_testdict.keys():
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assert "vqa" in results[key]
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if key == "IMG_2746":
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assert "marathon" in results[key]["vqa"][0].lower()
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if key == "IMG_2809":
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assert (
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"two" in results[key]["vqa"][1].lower() or "2" in results[key]["vqa"][1]
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)
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def test_clean_list_of_questions(mock_model):
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list_of_questions = [
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"What is happening in the image?",
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"",
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" ",
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None,
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"How many cars are in the image in total",
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]
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detector = ImageSummaryDetector(summary_model=mock_model, subdict={})
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prompt = detector.token_prompt_config["default"]["questions"]["prompt"]
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cleaned_questions = detector._clean_list_of_questions(list_of_questions, prompt)
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assert len(cleaned_questions) == 2
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assert cleaned_questions[0] == "What is happening in the image?"
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assert cleaned_questions[1] == "How many cars are in the image in total?"
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prompt = detector.token_prompt_config["concise"]["questions"]["prompt"]
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cleaned_questions = detector._clean_list_of_questions(list_of_questions, prompt)
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assert len(cleaned_questions) == 2
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assert cleaned_questions[0] == prompt + "What is happening in the image?"
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assert cleaned_questions[1] == prompt + "How many cars are in the image in total?"
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# Fast tests using mock model (no actual model loading)
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def test_image_summary_detector_init_mock(mock_model, get_testdict):
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"""Test detector initialization with mocked model."""
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detector = ImageSummaryDetector(summary_model=mock_model, subdict=get_testdict)
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assert detector.summary_model is mock_model
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assert len(detector.subdict) == 2
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def test_load_pil_if_needed_string(mock_model):
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"""Test loading image from file path."""
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detector = ImageSummaryDetector(summary_model=mock_model)
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# This will try to actually load a file, so we'll use a test image
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test_image_path = os.path.join(os.path.dirname(__file__), "data", "IMG_2746.png")
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if os.path.exists(test_image_path):
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img = detector._load_pil_if_needed(test_image_path)
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assert isinstance(img, Image.Image)
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assert img.mode == "RGB"
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def test_is_sequence_but_not_str(mock_model):
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"""Test sequence detection utility."""
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detector = ImageSummaryDetector(summary_model=mock_model)
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assert detector._is_sequence_but_not_str([1, 2, 3]) is True
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assert detector._is_sequence_but_not_str("string") is False
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assert detector._is_sequence_but_not_str(b"bytes") is False
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assert (
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detector._is_sequence_but_not_str({"a": 1}) is False
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) # dict is sequence-like but not handled as such
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def test_validate_analysis_type(mock_model):
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"""Test analysis type validation."""
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detector = ImageSummaryDetector(summary_model=mock_model)
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# Test valid types
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_, _, is_summary, is_questions = detector._validate_analysis_type(
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"summary", None, 10
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)
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assert is_summary is True
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assert is_questions is False
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_, _, is_summary, is_questions = detector._validate_analysis_type(
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"questions", ["What is this?"], 10
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)
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assert is_summary is False
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assert is_questions is True
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_, _, is_summary, is_questions = detector._validate_analysis_type(
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"summary_and_questions", ["What is this?"], 10
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)
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assert is_summary is True
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assert is_questions is True
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# Test invalid type
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with pytest.raises(ValueError):
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detector._validate_analysis_type("invalid", None, 10)
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# Test too many questions
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with pytest.raises(ValueError):
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detector._validate_analysis_type(
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"questions", ["Q" + str(i) for i in range(33)], 32
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)
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