def test_band_acquisition_pattern_invalid_negative_width(self):
expected = self.setup.getExpectedOutputMatrix(self._testMethodName)
self.actual = aqc.bandPattern(self.mask_size, -4, 1000, 0)
self.assertTrue(self.setup.matrixEqual(expected, self.actual))
def test_band_acquisition_pattern_width_larger_than_image(self):
expected = self.setup.getExpectedOutputMatrix(self._testMethodName)
self.actual = aqc.bandPattern(self.mask_size, 2000, 1000, 0)
self.assertTrue(self.setup.matrixEqual(expected, self.actual))
def test_ellipse_acquisition_pattern_horizontal_ellipse_bigger_than_image(
self):
expected = self.setup.getExpectedOutputMatrix(self._testMethodName)
self.actual = aqc.ellipsePattern(self.mask_size, 1500, 100, 0)
self.assertTrue(self.setup.matrixEqual(expected, self.actual))
def test_band_acquisition_pattern_width_is_small(self):
expected = self.setup.getExpectedOutputMatrix(self._testMethodName)
self.actual = aqc.bandPattern(self.mask_size, 30, 500, 0)
self.assertTrue(self.setup.matrixEqual(expected, self.actual))
def test_circle_acquisition_pattern_when_radius_is_greater_than_image(
self):
expected = self.setup.getExpectedOutputMatrix(self._testMethodName)
self.actual = aqc.circlePattern(self.mask_size, 1200)
self.assertTrue(self.setup.matrixEqual(expected, self.actual))
def test_ellipse_acquisition_pattern_centered_vertical_ellipse(self):
expected = self.setup.getExpectedOutputMatrix(self._testMethodName)
self.actual = aqc.ellipsePattern(self.mask_size, 100, 200, 0)
self.assertTrue(self.setup.matrixEqual(expected, self.actual))
def test_spiral_acquisition_pattern_sparsity_10(self):
expected = self.setup.getExpectedOutputMatrix(self._testMethodName)
self.actual = aqc.spiralPattern(self.mask_size, 10)
self.assertTrue(self.setup.matrixEqual(expected, self.actual))
def test_cartesian_pattern_60_percent(self):
expected = self.setup.getExpectedOutputMatrix(self._testMethodName)
self.actual = aqc.cartesianPattern(self.mask_size, 0.6)
self.assertTrue(self.setup.matrixEqual(expected, self.actual))
def test_radial_acquisition_pattern_360(self):
expected = self.setup.getExpectedOutputMatrix(self._testMethodName)
self.actual = aqc.radialPattern(self.mask_size, 360)
self.assertTrue(self.setup.matrixEqual(expected, self.actual))
def test_band_acquisition_pattern_angle_400(self):
expected = self.setup.getExpectedOutputMatrix(self._testMethodName)
self.actual = aqc.bandPattern(self.mask_size, 10, 500, 400)
self.assertTrue(self.setup.matrixEqual(expected, self.actual))
# Use this file as you wish to generate the images needed to answer the report
import src.project.Utilities as util
import numpy as np
import src.project.SelectiveImageAcquisition as sia
image = util.loadImage('images/brain.png')
rows, cols = image.shape
print(image.shape)
# code for cardiac cartesian
# mask = sia.cartesianPattern((rows, cols), 0.7)
mask = sia.circlePattern((rows, cols), 90)
shift_fft = util.getDFT(image)
filtered_image_fft = np.multiply(mask, shift_fft)
filtered_image = util.post_process_images(util.getImage(filtered_image_fft))
util.displayImage(filtered_image)
cardiac = util.loadImage("images/cardiac.jpg")
normal_cardiac = util.normalizeImage(cardiac)
dft_cardiac = util.getDFT(normal_cardiac)
write_dft = util.writableDFT(dft_cardiac)
util.saveMatrix("Cardiac_DFT.jpg", write_dft)
height, width = cardiac.shape
cardiac_size = np.array([height, width])
brain = util.loadImage("images/brain.png")
normal_brain = util.normalizeImage(brain)
dft_brain = util.getDFT(normal_brain)
#util.saveMatrix("Brain_DFT.jpg", dft_brain)
height, width = brain.shape
brain_size = np.array([height, width])
p1mask = aqc.bandPattern(cardiac_size, 15, 128, 35)
p1fmask = util.post_process_image(p1mask)
util.saveImage("p1fmask.jpg", p1fmask)
p1applied = util.applyMask(dft_cardiac, p1mask)
p1image = util.getImage(p1applied)
p1fimage = util.post_process_image(p1image)
util.saveImage('p1_Masked_Image.jpg', p1fimage)
p2mask1 = aqc.bandPattern(cardiac_size, 15, 128, 10)
p2applied1 = util.applyMask(dft_cardiac, p2mask1)
p2image1 = util.getImage(p2applied1)
p2fimage1 = util.post_process_image(p2image1)
util.saveImage("p2_Masked_Image_1.jpg", p2fimage1)
p2mask2 = aqc.bandPattern(cardiac_size, 10, 171, 135)
p2applied2 = util.applyMask(dft_cardiac, p2mask2)
# a = util.applyMask(img_copy, mask)
# b = util.writableDFT(a)
# c = util.normalizeImage(b)
# d = util.post_process_image(c)
# count += 1
# print(count)
# util.displayImage(d)
################# Part 3 #####################
img_copy2 = util.getDFT(img)
#mask_size2 = (h, w)
percent = .5
mask = sia.cartesianPattern(mask_size2, percent)
mask1 = sia.cartesianPattern(mask_size2, .05)
mask2 = sia.cartesianPattern(mask_size2, .15)
mask3 = sia.cartesianPattern(mask_size2, .35)
mask4 = sia.cartesianPattern(mask_size2, .64)
masks = (mask1, mask2, mask3, mask4)
count = 0
for mask in masks:
a = util.applyMask(img_copy2, mask)
b = util.writableDFT(a)
c = util.normalizeImage(b)
d = util.post_process_image(c)
count += 1