第1关:图像阈值分割
import cv2
import matplotlib.pyplot as plt
def thd():
filepath='/data/workspace/myshixun/task1/'
# 请根据左侧编程要求,完成图像阈值化操作:
########## Begin ##########
img = cv2.imread(filepath+'cat.jpg')
img = img[:,:,(2,1,0)]
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret1, thresh1 = cv2.threshold(img_gray, 150, 255, cv2.THRESH_BINARY)
ret2, thresh2 = cv2.threshold(img_gray, 150, 255, cv2.THRESH_BINARY_INV)
ret3, thresh3 = cv2.threshold(img_gray, 150, 255, cv2.THRESH_TRUNC)
ret4, thresh4 = cv2.threshold(img_gray, 150, 255, cv2.THRESH_TOZERO)
ret5, thresh5 = cv2.threshold(img_gray, 150, 255, cv2.THRESH_TOZERO_INV)
########## End ##########
# 作图并保存到指定路径
titles = ['Original Image', 'BINARY', 'BINARY_INV', 'TRUNC', 'TOZERO', 'TOZERO_INV']
images = [img, thresh1, thresh2, thresh3, thresh4, thresh5]
for i in range(6):
plt.subplot(2, 3, i + 1), plt.imshow(images[i], 'gray')
plt.title(titles[i])
plt.xticks([]), plt.yticks([])
plt.savefig(filepath+'out/threthold.png')
第2关:图像的平滑
import cv2
import matplotlib.pyplot as plt
# 使用图像平滑处理带噪声的图片
def flt():
filepath = '/data/workspace/myshixun/task2/'
# 请根据左侧编程要求,完成图像平滑操作:
########## Begin ##########
img=cv2.imread(filepath+"pic.png")
img = img[:,:,(2,1,0)]
res1 = cv2.blur(img, (5,5))
res2 = cv2.GaussianBlur(img,(5,5),0,0)
res3 = cv2.boxFilter(img, -1, (5,5), False)
res4 = cv2.medianBlur(img, 5)
########## End ##########
# 作图并保存到指定路径
titles = ['Blur', 'GaussianBlur', 'boxFilter', 'medianBlur']
images = [res1, res2, res3, res4]
# 分别画出四个子图,并保存为filter.png
for i in range(4):
plt.subplot(2, 2, i + 1), plt.imshow(images[i], 'gray')
plt.title(titles[i])
plt.xticks([]), plt.yticks([])
plt.savefig(filepath+'out/filter.png')
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