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117 lines
4.0 KiB
Python
117 lines
4.0 KiB
Python
import numpy as np
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import pytest
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from uniface.attribute import AgeGender
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@pytest.fixture
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def age_gender_model():
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return AgeGender()
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@pytest.fixture
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def mock_image():
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return np.random.randint(0, 255, (640, 640, 3), dtype=np.uint8)
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@pytest.fixture
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def mock_bbox():
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return [100, 100, 300, 300]
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def test_model_initialization(age_gender_model):
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assert age_gender_model is not None, "AgeGender model initialization failed."
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def test_prediction_output_format(age_gender_model, mock_image, mock_bbox):
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gender, age = age_gender_model.predict(mock_image, mock_bbox)
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assert isinstance(gender, str), f"Gender should be string, got {type(gender)}"
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assert isinstance(age, int), f"Age should be int, got {type(age)}"
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def test_gender_values(age_gender_model, mock_image, mock_bbox):
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gender, age = age_gender_model.predict(mock_image, mock_bbox)
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assert gender in ["Male", "Female"], f"Gender should be 'Male' or 'Female', got '{gender}'"
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def test_age_range(age_gender_model, mock_image, mock_bbox):
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gender, age = age_gender_model.predict(mock_image, mock_bbox)
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assert 0 <= age <= 120, f"Age should be between 0 and 120, got {age}"
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def test_different_bbox_sizes(age_gender_model, mock_image):
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test_bboxes = [
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[50, 50, 150, 150],
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[100, 100, 300, 300],
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[50, 50, 400, 400],
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]
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for bbox in test_bboxes:
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gender, age = age_gender_model.predict(mock_image, bbox)
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assert gender in ["Male", "Female"], f"Failed for bbox {bbox}"
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assert 0 <= age <= 120, f"Age out of range for bbox {bbox}"
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def test_different_image_sizes(age_gender_model, mock_bbox):
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test_sizes = [(480, 640, 3), (720, 1280, 3), (1080, 1920, 3)]
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for size in test_sizes:
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mock_image = np.random.randint(0, 255, size, dtype=np.uint8)
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gender, age = age_gender_model.predict(mock_image, mock_bbox)
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assert gender in ["Male", "Female"], f"Failed for image size {size}"
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assert 0 <= age <= 120, f"Age out of range for image size {size}"
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def test_consistency(age_gender_model, mock_image, mock_bbox):
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gender1, age1 = age_gender_model.predict(mock_image, mock_bbox)
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gender2, age2 = age_gender_model.predict(mock_image, mock_bbox)
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assert gender1 == gender2, "Same input should produce same gender prediction"
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assert age1 == age2, "Same input should produce same age prediction"
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def test_bbox_list_format(age_gender_model, mock_image):
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bbox_list = [100, 100, 300, 300]
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gender, age = age_gender_model.predict(mock_image, bbox_list)
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assert gender in ["Male", "Female"], "Should work with bbox as list"
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assert 0 <= age <= 120, "Age should be in valid range"
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def test_bbox_array_format(age_gender_model, mock_image):
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bbox_array = np.array([100, 100, 300, 300])
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gender, age = age_gender_model.predict(mock_image, bbox_array)
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assert gender in ["Male", "Female"], "Should work with bbox as numpy array"
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assert 0 <= age <= 120, "Age should be in valid range"
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def test_multiple_predictions(age_gender_model, mock_image):
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bboxes = [
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[50, 50, 150, 150],
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[200, 200, 350, 350],
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[400, 400, 550, 550],
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]
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results = []
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for bbox in bboxes:
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gender, age = age_gender_model.predict(mock_image, bbox)
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results.append((gender, age))
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assert len(results) == 3, "Should have 3 predictions"
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for gender, age in results:
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assert gender in ["Male", "Female"]
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assert 0 <= age <= 120
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def test_age_is_positive(age_gender_model, mock_image, mock_bbox):
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for _ in range(5):
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gender, age = age_gender_model.predict(mock_image, mock_bbox)
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assert age >= 0, f"Age should be non-negative, got {age}"
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def test_output_format_for_visualization(age_gender_model, mock_image, mock_bbox):
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gender, age = age_gender_model.predict(mock_image, mock_bbox)
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text = f"{gender}, {age}y"
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assert isinstance(text, str), "Should be able to format as string"
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assert "Male" in text or "Female" in text, "Text should contain gender"
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assert "y" in text, "Text should contain 'y' for years"
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