Remove obsolete code
This commit is contained in:
Matthias Bisping
parent
dd6ab94aa2
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4772e3037c
223
test/fixtures/page_generation/page.py
vendored
223
test/fixtures/page_generation/page.py
vendored
@ -1,45 +1,12 @@
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import random
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from typing import Tuple
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from typing import Tuple, Union
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import albumentations as A
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import cv2 as cv
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import numpy as np
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import pytest
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from PIL import Image, ImageOps
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# transform = A.Compose(
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# [
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# # brightness and contrast transforms
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# A.OneOf(
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# [
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# A.RandomGamma(p=0.2),
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# A.RandomBrightnessContrast(p=0.2, brightness_limit=0.05, contrast_limit=0.05),
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# ],
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# p=0.5,
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# ),
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# # color transforms
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# A.SomeOf(
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# [
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# A.ColorJitter(p=1),
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# A.RGBShift(p=1, r_shift_limit=0.3, g_shift_limit=0.3, b_shift_limit=0.3),
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# A.ChannelShuffle(p=1),
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# ],
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# p=1.0,
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# n=3, # 3 => all
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# ),
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# # # blurring and sharpening transforms
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# # A.OneOf(
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# # [
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# # A.GaussianBlur(p=0.05),
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# # A.MotionBlur(p=0.05, blur_limit=21),
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# # A.Sharpen(p=0.05),
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# # ],
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# # p=0.0,
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# # ),
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# ]
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# )
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from PIL.Image import Transpose
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#
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# transform = A.Compose(
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# [
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@ -96,8 +63,42 @@ from PIL.Image import Transpose
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# ],
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# p=0.5,
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# )
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from funcy import juxt, compose, identity
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from cv_analysis.locations import TEST_PAGE_TEXTURES_DIR
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# transform = A.Compose(
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# [
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# # brightness and contrast transforms
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# A.OneOf(
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# [
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# A.RandomGamma(p=0.2),
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# A.RandomBrightnessContrast(p=0.2, brightness_limit=0.05, contrast_limit=0.05),
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# ],
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# p=0.5,
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# ),
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# # color transforms
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# A.SomeOf(
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# [
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# A.ColorJitter(p=1),
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# A.RGBShift(p=1, r_shift_limit=0.3, g_shift_limit=0.3, b_shift_limit=0.3),
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# A.ChannelShuffle(p=1),
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# ],
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# p=1.0,
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# n=3, # 3 => all
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# ),
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# # # blurring and sharpening transforms
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# # A.OneOf(
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# # [
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# # A.GaussianBlur(p=0.05),
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# # A.MotionBlur(p=0.05, blur_limit=21),
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# # A.Sharpen(p=0.05),
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# # ],
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# # p=0.0,
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# # ),
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# ]
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# )
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transform = A.Compose(
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[
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# A.ColorJitter(p=1),
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@ -158,8 +159,8 @@ def color_name(request):
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@pytest.fixture(
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params=[
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"smooth",
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"coarse",
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# "smooth",
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# "coarse",
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"neutral",
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]
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)
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@ -186,19 +187,6 @@ def random_flip(image):
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return image
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# @pytest.fixture
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# def color(color_name):
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# return {
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# "brown": (0.5, 0.3, 0.2),
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# "yellow": (0.5, 0.5, 0.0),
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# "sepia": (173, 155, 109),
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# "gray": (0.3, 0.3, 0.3),
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# "white": (0.0, 0.0, 0.0),
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# "light_red": (0.5, 0.0, 0.0),
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# "light_blue": (0.0, 0.0, 0.5),
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# }[color_name]
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@pytest.fixture
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def color(color_name):
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return {
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@ -211,47 +199,54 @@ def color(color_name):
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}[color_name]
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# @pytest.fixture
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# def texture_fn(texture_name, size):
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# if texture_name == "smooth":
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# fn = blur
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# elif texture_name == "coarse":
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# fn = compose(overlay, juxt(blur, sharpen))
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# else:
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# fn = identity
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#
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# return fn
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#
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#
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# def blur(image: np.ndarray):
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# return cv.blur(image, (3, 3))
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#
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#
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# def sharpen(image: np.ndarray):
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# return cv.filter2D(image, -1, np.array([[-1, -1, -1], [-1, 6, -1], [-1, -1, -1]]))
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#
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#
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# def overlay(images, mode=np.sum):
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# assert mode in [np.sum, np.max]
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# images = np.stack(list(images))
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# image = mode(images, axis=0)
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# image = (image / image.max() * 255).astype(np.uint8)
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# return image
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#
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#
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# @pytest.fixture
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# def texture(texture_fn, size, color):
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# noise_arr = np.random.rand(*size) * 255
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# noise_arr = color_shift_noise(noise_arr, color)
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#
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# noise_arr = zero_out_below_threshold(noise_arr, 0.4)
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# noise_arr = texture_fn(noise_arr)
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# assert noise_arr.max() <= 255
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#
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# noise_img = Image.fromarray(noise_arr)
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# # noinspection PyTypeChecker
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# assert np.equal(noise_arr, np.array(noise_img)).all()
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# return noise_img
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@pytest.fixture
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def texture_fn(texture_name, size):
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if texture_name == "smooth":
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fn = blur
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elif texture_name == "coarse":
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fn = compose(overlay, juxt(blur, sharpen))
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else:
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fn = identity
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return normalize_image_function(fn)
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def blur(image: np.ndarray):
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return cv.blur(image, (3, 3))
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def normalize_image_format_to_array(image: Union[np.ndarray, Image.Image]):
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if isinstance(image, Image.Image):
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return np.array(image)
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return image
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def normalize_image_format_to_pil(image: Union[np.ndarray, Image.Image]):
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if isinstance(image, np.ndarray):
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return Image.fromarray(image)
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return image
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def normalize_image_function(func):
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def inner(image):
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image = normalize_image_format_to_array(image)
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image = func(image)
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image = normalize_image_format_to_pil(image)
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return image
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return inner
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def sharpen(image: np.ndarray):
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return cv.filter2D(image, -1, np.array([[-1, -1, -1], [-1, 6, -1], [-1, -1, -1]]))
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def overlay(images, mode=np.sum):
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assert mode in [np.sum, np.max]
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images = np.stack(list(images))
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image = mode(images, axis=0)
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image = (image / image.max() * 255).astype(np.uint8)
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return image
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@pytest.fixture
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@ -271,25 +266,6 @@ def tint_image(src, color="#FFFFFF"):
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return result
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# def color_shift_noise(noise: np.ndarray, color: Color):
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# """Creates a 3-tensor from a 2-tensor by stacking the 2-tensor three times weighted by the color tuple."""
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# assert noise.ndim == 2
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# assert isinstance(color, tuple)
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# assert max(color) <= 255
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# assert noise.max() <= 255
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#
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# color = np.array(color)
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# weights = color / color.sum()
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# assert max(weights) <= 1
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#
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# alpha_channel = np.ones(noise.shape) * 255
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# colored_noise = np.stack([noise * weight for weight in weights] + [alpha_channel], axis=-1).astype(np.uint8)
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#
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# assert colored_noise.shape == (*noise.shape, 4)
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#
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# return colored_noise
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def color_shift_array(image: np.ndarray, color: Color):
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"""Creates a 3-tensor from a 2-tensor by stacking the 2-tensor three times weighted by the color tuple."""
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assert image.ndim == 3
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@ -302,9 +278,6 @@ def color_shift_array(image: np.ndarray, color: Color):
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weights = color / color.sum() / 10
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assert max(weights) <= 1
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# alpha_channel = np.ones(image.shape) * 255
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# colored_noise = np.stack([image * weight for weight in weights] + [alpha_channel], axis=-1).astype(np.uint8)
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# colored = np.column_stack([image * weights] + [alpha_channel]).astype(np.uint8)
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colored = (image * weights).astype(np.uint8)
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assert colored.shape == image.shape
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@ -312,18 +285,6 @@ def color_shift_array(image: np.ndarray, color: Color):
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return colored
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# def zero_out_below_threshold(texture, threshold):
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# assert texture.max() <= 255
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#
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# texture[:, :, 3] = 100
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#
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# threshold = int(texture[:, :, 0:3].sum(axis=2).max() * threshold)
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# threshold_mask = texture[:, :, 0:3].sum(axis=2) >= threshold
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# texture[~threshold_mask] = [0, 0, 0, 50]
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#
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# return texture
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@pytest.fixture
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def size(dpi, orientation):
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if orientation == "portrait":
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@ -336,15 +297,6 @@ def size(dpi, orientation):
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return size
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# @pytest.fixture
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# def blank_page(size, texture) -> np.ndarray:
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# """Creates a blank page with a given orientation and dpi."""
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# page = Image.fromarray(np.zeros((*size, 4), dtype=np.uint8) * 255)
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# page = superimpose_texture_with_transparency(page, texture)
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# # page = transform(image=page)["image"]
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# return page
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#
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def superimpose_texture_with_transparency(page: Image, texture: Image) -> Image:
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"""Superimposes a noise image with transparency onto a page image."""
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assert page.mode == "RGB"
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@ -355,7 +307,8 @@ def superimpose_texture_with_transparency(page: Image, texture: Image) -> Image:
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@pytest.fixture
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def blank_page(texture) -> np.ndarray:
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def blank_page(texture, texture_fn) -> np.ndarray:
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"""Creates a blank page with a given orientation and dpi."""
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page = random_flip(texture)
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page = texture_fn(page)
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return page
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