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from pathlib import Path
from typing import Dict
import pytest
from PIL import Image
from pixelmatch.contrib import PIL
from pixelmatch import pixelmatch
FIXTURES_PATH = Path(__file__).parent / "fixtures"
OPTIONS = {"threshold": 0.05}
def read_img(name: str):
return Image.open(FIXTURES_PATH / f"{name}.png")
def pil_to_flatten_data(img):
"""
Convert data from [(R1, G1, B1, A1), (R2, G2, B2, A2)] to [R1, G1, B1, A1, R2, G2, B2, A2]
"""
return [x for p in img.convert("RGBA").getdata() for x in p]
testdata = [
["1a", "1b", "1diff", OPTIONS, 143],
[
"1a",
"1b",
"1diffmask",
{"threshold": 0.05, "includeAA": False, "diff_mask": True},
143,
],
["1a", "1a", "1emptydiffmask", {"threshold": 0, "diff_mask": True}, 0],
[
"2a",
"2b",
"2diff",
{
"threshold": 0.05,
"alpha": 0.5,
"aa_color": [0, 192, 0],
"diff_color": [255, 0, 255],
},
12437,
],
["3a", "3b", "3diff", OPTIONS, 212],
["4a", "4b", "4diff", OPTIONS, 36049],
["5a", "5b", "5diff", OPTIONS, 0],
["6a", "6b", "6diff", OPTIONS, 51],
["6a", "6a", "6empty", {"threshold": 0}, 0],
["7a", "7b", "7diff", OPTIONS, 9856],
]
@pytest.mark.parametrize(
"img_path_1,img_path_2,diff_path,options,expected_mismatch", testdata
)
def test_pixelmatch(
img_path_1: str,
img_path_2: str,
diff_path: str,
options: Dict,
expected_mismatch: int,
benchmark,
):
img1 = read_img(img_path_1)
img2 = read_img(img_path_2)
width, height = img1.size
img1_data = pil_to_flatten_data(img1)
img2_data = pil_to_flatten_data(img2)
diff_data = [0.0] * len(img1_data)
mismatch = benchmark(
pixelmatch, img1_data, img2_data, width, height, diff_data, **options
)
mismatch2 = pixelmatch(img1_data, img2_data, width, height, None, **options)
expected_diff = read_img(diff_path)
assert diff_data == pil_to_flatten_data(expected_diff), "diff image"
assert mismatch == expected_mismatch, "number of mismatched pixels"
assert mismatch == mismatch2, "number of mismatched pixels without diff"
@pytest.mark.parametrize(
"img_path_1,img_path_2,diff_path,options,expected_mismatch", testdata
)
def test_pixelmatch_failfast(
img_path_1: str,
img_path_2: str,
diff_path: str,
options: Dict,
expected_mismatch: int,
benchmark,
):
img1 = read_img(img_path_1)
img2 = read_img(img_path_2)
width, height = img1.size
img1_data = pil_to_flatten_data(img1)
img2_data = pil_to_flatten_data(img2)
if expected_mismatch:
assert (
benchmark(
pixelmatch,
img1_data,
img2_data,
width,
height,
fail_fast=True,
**options,
)
== 1
)
@pytest.mark.parametrize(
"img_path_1,img_path_2,diff_path,options,expected_mismatch", testdata
)
def test_PIL_pixelmatch(
img_path_1: str,
img_path_2: str,
diff_path: str,
options: Dict,
expected_mismatch: int,
benchmark,
):
img1 = read_img(img_path_1)
img2 = read_img(img_path_2)
diff_data = Image.new("RGBA", img1.size)
mismatch = benchmark(PIL.pixelmatch, img1, img2, diff_data, **options)
mismatch2 = PIL.pixelmatch(img1, img2, **options)
assert pil_to_flatten_data(diff_data) == pil_to_flatten_data(
read_img(diff_path)
), "diff image"
assert mismatch == expected_mismatch, "number of mismatched pixels"
assert mismatch == mismatch2, "number of mismatched pixels without diff"
|
