112 lines
3.1 KiB
Python
112 lines
3.1 KiB
Python
import pytest
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from pathlib import Path
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from analyzer import is_blurry
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def make_test_image(tmp_path, color=(200, 200, 200)):
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from PIL import Image
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img = Image.new("RGB", (100, 100), color=color)
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p = tmp_path / "test.jpg"
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img.save(p)
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return str(p)
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def test_solid_color_image_is_blurry(tmp_path):
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path = make_test_image(tmp_path)
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assert is_blurry(path, threshold=100) is True
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def test_normal_image_is_not_blurry(tmp_path):
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from PIL import Image, ImageDraw
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img = Image.new("RGB", (100, 100), color=(255, 255, 255))
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draw = ImageDraw.Draw(img)
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for i in range(0, 100, 2):
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draw.line([(i, 0), (i, 100)], fill=(0, 0, 0), width=1)
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p = tmp_path / "sharp.jpg"
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img.save(p)
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assert is_blurry(str(p), threshold=100) is False
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from analyzer import is_overexposed, is_underexposed
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def test_white_image_is_overexposed(tmp_path):
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path = make_test_image(tmp_path, color=(255, 255, 255))
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assert is_overexposed(path, threshold=240) is True
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def test_dark_image_is_underexposed(tmp_path):
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path = make_test_image(tmp_path, color=(10, 10, 10))
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assert is_underexposed(path, threshold=30) is True
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def test_normal_image_is_neither(tmp_path):
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path = make_test_image(tmp_path, color=(128, 128, 128))
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assert is_overexposed(path, threshold=240) is False
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assert is_underexposed(path, threshold=30) is False
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from analyzer import find_duplicates
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def make_gradient_image(tmp_path, name="gradient.jpg"):
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from PIL import Image
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img = Image.new("L", (100, 100))
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pixels = img.load()
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for y in range(100):
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for x in range(100):
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pixels[x, y] = x * 255 // 100
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p = tmp_path / name
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img.convert("RGB").save(p)
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return str(p)
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def make_diagonal_image(tmp_path, name="diagonal.jpg"):
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from PIL import Image
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img = Image.new("L", (100, 100))
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pixels = img.load()
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for y in range(100):
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for x in range(100):
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pixels[x, y] = 255 if x > y else 0
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p = tmp_path / name
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img.convert("RGB").save(p)
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return str(p)
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def test_identical_images_are_duplicates(tmp_path):
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p1 = make_gradient_image(tmp_path, "img1.jpg")
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import shutil
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p2 = tmp_path / "copy.jpg"
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shutil.copy(p1, p2)
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groups = find_duplicates([p1, str(p2)], threshold=8)
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assert len(groups) == 1
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assert len(groups[0]) == 2
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def test_different_images_are_not_duplicates(tmp_path):
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p1 = make_gradient_image(tmp_path, "gradient.jpg")
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p2 = make_diagonal_image(tmp_path, "diagonal.jpg")
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groups = find_duplicates([p1, p2], threshold=8)
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assert len(groups) == 0
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from analyzer import analyze_folder
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def test_analyze_folder_returns_results(tmp_path):
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make_test_image(tmp_path, color=(128, 128, 128))
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from PIL import Image
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white = tmp_path / "white.jpg"
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Image.new("RGB", (100, 100), color=(255, 255, 255)).save(white)
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results = analyze_folder(
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folder=str(tmp_path),
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blur_threshold=100,
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over_threshold=240,
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under_threshold=30,
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dup_threshold=8,
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use_ai=False,
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)
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reasons_flat = [r for item in results for r in item["reasons"]]
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assert "ueberbelichtet" in reasons_flat
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