Python/digital_image_processing/test_digital_image_processing.py

71 lines
2.1 KiB
Python
Raw Normal View History

2019-08-08 15:59:15 +00:00
"""
PyTest's for Digital Image Processing
"""
import digital_image_processing.edge_detection.canny as canny
import digital_image_processing.filters.gaussian_filter as gg
import digital_image_processing.filters.median_filter as med
import digital_image_processing.filters.sobel_filter as sob
import digital_image_processing.filters.convolve as conv
import digital_image_processing.change_contrast as cc
import digital_image_processing.convert_to_negative as cn
2019-08-08 15:59:15 +00:00
from cv2 import imread, cvtColor, COLOR_BGR2GRAY
from numpy import array, uint8
from PIL import Image
img = imread(r"digital_image_processing/image_data/lena_small.jpg")
2019-08-08 15:59:15 +00:00
gray = cvtColor(img, COLOR_BGR2GRAY)
# Test: convert_to_negative()
def test_convert_to_negative():
negative_img = cn.convert_to_negative(img)
# assert negative_img array for at least one True
assert negative_img.any()
2019-08-08 15:59:15 +00:00
# Test: change_contrast()
def test_change_contrast():
with Image.open("digital_image_processing/image_data/lena_small.jpg") as img:
2019-08-08 15:59:15 +00:00
# Work around assertion for response
assert str(cc.change_contrast(img, 110)).startswith(
"<PIL.Image.Image image mode=RGB size=100x100 at"
2019-08-08 15:59:15 +00:00
)
# canny.gen_gaussian_kernel()
def test_gen_gaussian_kernel():
resp = canny.gen_gaussian_kernel(9, sigma=1.4)
# Assert ambiguous array
assert resp.all()
# canny.py
def test_canny():
canny_img = imread("digital_image_processing/image_data/lena_small.jpg", 0)
2019-08-08 15:59:15 +00:00
# assert ambiguos array for all == True
assert canny_img.all()
canny_array = canny.canny(canny_img)
# assert canny array for at least one True
assert canny_array.any()
# filters/gaussian_filter.py
def test_gen_gaussian_kernel_filter():
assert gg.gaussian_filter(gray, 5, sigma=0.9).all()
def test_convolve_filter():
# laplace diagonals
Laplace = array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]])
res = conv.img_convolve(gray, Laplace).astype(uint8)
assert res.any()
def test_median_filter():
assert med.median_filter(gray, 3).any()
def test_sobel_filter():
grad, theta = sob.sobel_filter(gray)
assert grad.any() and theta.any()