Refactoring: Move

Move image operations such as blurring into their own module.

cv_analysis/utils/image_operations.py

@@ -0,0 +1,51 @@
+from typing import Tuple
+
+import cv2 as cv
+import numpy as np
+from PIL import ImageOps
+
+Color = Tuple[int, int, int]
+
+
+def blur(image: np.ndarray):
+    return cv.blur(image, (3, 3))
+
+
+def sharpen(image: np.ndarray):
+    return cv.filter2D(image, -1, np.array([[-1, -1, -1], [-1, 6, -1], [-1, -1, -1]]))
+
+
+def overlay(images, mode=np.sum):
+    assert mode in [np.sum, np.max]
+    images = np.stack(list(images))
+    image = mode(images, axis=0)
+    image = (image / image.max() * 255).astype(np.uint8)
+    return image
+
+
+def tint_image(src, color="#FFFFFF"):
+    src.load()
+    r, g, b, alpha = src.split()
+    gray = ImageOps.grayscale(src)
+    result = ImageOps.colorize(gray, (0, 0, 0), color)
+    result.putalpha(alpha)
+    return result
+
+
+def color_shift_array(image: np.ndarray, color: Color):
+    """Creates a 3-tensor from a 2-tensor by stacking the 2-tensor three times weighted by the color tuple."""
+    assert image.ndim == 3
+    assert image.shape[-1] == 3
+    assert isinstance(color, tuple)
+    assert max(color) <= 255
+    assert image.max() <= 255
+
+    color = np.array(color)
+    weights = color / color.sum() / 10
+    assert max(weights) <= 1
+
+    colored = (image * weights).astype(np.uint8)
+
+    assert colored.shape == image.shape
+
+    return colored

test/fixtures/page_generation/page.py

@@ -12,10 +12,9 @@ from pathlib import Path
 from typing import Tuple, Iterable, List
 
 import blend_modes
-import cv2 as cv
 import numpy as np
 import pytest
-from PIL import Image, ImageOps, ImageFont, ImageDraw, ImageEnhance
+from PIL import Image, ImageFont, ImageDraw, ImageEnhance
 from PIL.Image import Transpose
 from faker import Faker
 from loguru import logger
@@ -24,6 +23,7 @@ from matplotlib.colors import ListedColormap
 
 from cv_analysis.utils import star, rconj, conj
 from cv_analysis.utils.conversion import normalize_image_format_to_array, normalize_image_format_to_pil
+from cv_analysis.utils.image_operations import blur, sharpen, overlay
 from cv_analysis.utils.merging import merge_related_rectangles
 from cv_analysis.utils.postprocessing import remove_overlapping, remove_included
 from cv_analysis.utils.spacial import area
@@ -70,9 +70,6 @@ from cv_analysis.utils.display import show_image
 from cv_analysis.utils.rectangle import Rectangle
 
 
-Color = Tuple[int, int, int]
-
-
 @pytest.fixture(
     params=[
         # "rough_grain",
@@ -176,10 +173,6 @@ def texture_fn(texture_name, size):
     return normalize_image_function(fn)
 
 
-def blur(image: np.ndarray):
-    return cv.blur(image, (3, 3))
-
-
 def normalize_image_function(func):
     def inner(image):
         image = normalize_image_format_to_array(image)
@@ -190,18 +183,6 @@ def normalize_image_function(func):
     return inner
 
 
-def sharpen(image: np.ndarray):
-    return cv.filter2D(image, -1, np.array([[-1, -1, -1], [-1, 6, -1], [-1, -1, -1]]))
-
-
-def overlay(images, mode=np.sum):
-    assert mode in [np.sum, np.max]
-    images = np.stack(list(images))
-    image = mode(images, axis=0)
-    image = (image / image.max() * 255).astype(np.uint8)
-    return image
-
-
 @pytest.fixture
 def texture(tinted_blank_page, base_texture):
     texture = superimpose_texture_with_transparency(base_texture, tinted_blank_page)
@@ -222,34 +203,6 @@ def blank_page(size, color, color_intensity):
     return page
 
 
-def tint_image(src, color="#FFFFFF"):
-    src.load()
-    r, g, b, alpha = src.split()
-    gray = ImageOps.grayscale(src)
-    result = ImageOps.colorize(gray, (0, 0, 0), color)
-    result.putalpha(alpha)
-    return result
-
-
-def color_shift_array(image: np.ndarray, color: Color):
-    """Creates a 3-tensor from a 2-tensor by stacking the 2-tensor three times weighted by the color tuple."""
-    assert image.ndim == 3
-    assert image.shape[-1] == 3
-    assert isinstance(color, tuple)
-    assert max(color) <= 255
-    assert image.max() <= 255
-
-    color = np.array(color)
-    weights = color / color.sum() / 10
-    assert max(weights) <= 1
-
-    colored = (image * weights).astype(np.uint8)
-
-    assert colored.shape == image.shape
-
-    return colored
-
-
 @pytest.fixture
 def size(dpi, orientation):
     if orientation == "portrait":