def high_pass_filter_process(imagename):
image_name1 = "../../homework4/project4/" + imagename
result = "../../homework4/result2" + imagename[:5] + ".png"
result2 = "../../homework4/result3" + imagename[:5] + "1.png"
tool = basic_cv_tool(image_name1)
img = tool.ImageRead(image_name1)
img1 = tool.laplace_filter(img)
img2 = tool.sobel_filter(img)
img3 = tool.unsharp_mask_filter(img, 0.5)
img4 = tool.canny(img)
plt.figure(figsize=(16, 4))
p1 = plt.subplot(141)
p1.set_title('laplace', fontsize=11)
p1.imshow(img1, cmap='gray')
p2 = plt.subplot(142)
p2.set_title('sobel', fontsize=11)
p2.imshow(img2, cmap='gray')
p3 = plt.subplot(143)
p3.set_title('unsharp', fontsize=11)
p3.imshow(img3, cmap='gray')
p3 = plt.subplot(144)
p3.set_title('canny', fontsize=11)
p3.imshow(img4, cmap='gray')
plt.savefig(result)
res = np.hstack((img1, img2, img3, img4))
cv2.imwrite(result2, res)
def task1(imagename, filtername):
image_name1 = "../../homework5/project5/" + imagename
result = "../../homework5/result1" + filtername + imagename[:5] + ".png"
tool = basic_cv_tool(image_name1)
img = tool.ImageRead(image_name1)
f = np.fft.fftshift(np.fft.fft2(img))
s = np.log(np.abs(f))
if filtername == 'butterworth':
img1 = tool.BLPF(img, 25, 2)
f1 = np.fft.fftshift(np.fft.fft2(img1))
s1 = np.log(np.abs(f1))
img2 = tool.BLPF(img, 50, 2)
f2 = np.fft.fftshift(np.fft.fft2(img2))
s2 = np.log(np.abs(f2))
img3 = tool.BLPF(img, 75, 2)
f3 = np.fft.fftshift(np.fft.fft2(img3))
s3 = np.log(np.abs(f3))
else:
img1 = tool.GLPF(img, 25, 2)
f1 = np.fft.fftshift(np.fft.fft2(img1))
s1 = np.log(np.abs(f1))
img2 = tool.GLPF(img, 50, 2)
f2 = np.fft.fftshift(np.fft.fft2(img2))
s2 = np.log(np.abs(f2))
img3 = tool.GLPF(img, 75, 2)
f3 = np.fft.fftshift(np.fft.fft2(img3))
s3 = np.log(np.abs(f3))
plt.figure(figsize=(16, 8))
p = plt.subplot(241)
p.set_title('original image', fontsize=11)
p.imshow(img, cmap='gray')
p1 = plt.subplot(242)
p1.set_title(filtername + ' filter, 25', fontsize=11)
p1.imshow(img1, cmap='gray')
p2 = plt.subplot(243)
p2.set_title(filtername + ' filter, 50', fontsize=11)
p2.imshow(img2, cmap='gray')
p3 = plt.subplot(244)
p3.set_title(filtername + ' filter, 75', fontsize=11)
p3.imshow(img3, cmap='gray')
pp = plt.subplot(245)
pp.set_title('original image', fontsize=11)
pp.imshow(s, cmap='gray')
p4 = plt.subplot(246)
p4.set_title(filtername + ' filter, 25', fontsize=11)
plt.imshow(s1, cmap='gray')
p5 = plt.subplot(247)
p5.set_title(filtername + ' filter, 50', fontsize=11)
p5.imshow(s2, cmap='gray')
p6 = plt.subplot(248)
p6.set_title(filtername + ' filter, 75', fontsize=11)
p6.imshow(s3, cmap='gray')
plt.savefig(result)
print(filtername, " 25: ", tool.Power_spectrum_ratio(img, img1))
print(filtername, " 25: ", tool.Power_spectrum_ratio(img, img2))
print(filtername, " 25: ", tool.Power_spectrum_ratio(img, img3))
def task3(imagename, k):
image_name1 = "../../homework5/project5/" + imagename
result = "../../homework5/result3" + imagename[:5] + ".png"
result2 = "../../homework5/result3" + imagename[:5] + "enhance.png"
tool = basic_cv_tool(image_name1)
img = tool.ImageRead(image_name1)
f = np.fft.fftshift(np.fft.fft2(img))
s = np.log(np.abs(f))
img1 = tool.LHPF(img, 25, 2)
f1 = np.fft.fftshift(np.fft.fft2(img1))
s1 = np.log(np.abs(f1))
img2 = tool.Unsharp_Masking(img, 25, 2, k)
f2 = np.fft.fftshift(np.fft.fft2(img2))
s2 = np.log(np.abs(f2))
plt.figure(figsize=(12, 8))
p = plt.subplot(231)
p.set_title('original image', fontsize=11)
p.imshow(img, cmap='gray')
p1 = plt.subplot(232)
p1.set_title('Laplacian', fontsize=11)
p1.imshow(img1, cmap='gray')
p2 = plt.subplot(233)
p2.set_title('Unsharp Masking', fontsize=11)
p2.imshow(img2, cmap='gray')
p3 = plt.subplot(234)
p3.set_title('original image', fontsize=11)
p3.imshow(s, cmap='gray')
pp = plt.subplot(235)
pp.set_title('Laplacian', fontsize=11)
pp.imshow(s1, cmap='gray')
p4 = plt.subplot(236)
p4.set_title('Unsharp Masking', fontsize=11)
plt.imshow(s2, cmap='gray')
plt.savefig(result)
plt.figure(figsize=(12, 4))
p = plt.subplot(131)
p.set_title('original image', fontsize=11)
p.imshow(img, cmap='gray')
p1 = plt.subplot(132)
p1.set_title('Laplacian enhance', fontsize=11)
p1.imshow(img + 0.5 * img1, cmap='gray')
print(img1)
p2 = plt.subplot(133)
p2.set_title('Unsharp Masking enhance', fontsize=11)
p2.imshow(img2, cmap='gray')
plt.savefig(result2)
def mid(imagename):
image_name1 = "../../homework4/project4/" + imagename
result = "../../homework4/result2" + imagename[:5] + ".png"
result2 = "../../homework4/result2" + imagename[:5] + "1.png"
tool = basic_cv_tool(image_name1)
img = tool.ImageRead(image_name1)
img1 = tool.MediumFilter(img, 3)
img2 = tool.MediumFilter(img, 5)
img3 = tool.MediumFilter(img, 7)
plt.figure(figsize=(16, 5))
p1 = plt.subplot(131)
p1.set_title('midfilter, 3x3', fontsize=11)
p1.imshow(img1, cmap='gray')
p2 = plt.subplot(132)
p2.set_title('midfilter, 5x5', fontsize=11)
p2.imshow(img2, cmap='gray')
p3 = plt.subplot(133)
p3.set_title('midfilter, 7x7', fontsize=11)
p3.imshow(img3, cmap='gray')
plt.savefig(result)
res = np.hstack((img1, img2, img3))
cv2.imwrite(result2, res)
import sys
import os
sys.path.remove('/opt/ros/kinetic/lib/python2.7/dist-packages')
lib_path = os.path.abspath(os.path.join(sys.path[0], '..'))
sys.path.append(lib_path)
from src.basic_cv_tool import *
image_2_name = '../../homework1/elain1.bmp'
tool = basic_cv_tool(image_2_name)
img = tool.ImageRead(image_2_name)
mean = tool.image_average(img)
var = tool.image_variance(img)
print(mean)
print(var)