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Sample.py
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# pip install opencv-python -i https://pypi.tuna.tsinghua.edu.cn/simple/
# pip install numpy
#=======================class1=====================================
# 相对路径：
# import cv2
# # img = cv2.imread('./b.jpg')
# # print(np.dtype(img))
# # print(img.shape)
# # print(img.size)
# # print(img.size())
# import numpy as np
# #绝对路径
# img = cv2.imread('/mnt/VM-UNet/b.jpg')
# print(type(img))
# print(img.shape)
# print(img.size)
#=======================class2=====================================
import numpy as np
import cv2
# img1 = np.random.randint(0,256,size=[3,4], dtype=np.uint8)
# print(img1) #[3,4]
# img2 = np.random.randint(0,256,size=[4,3],dtype=np.uint8)
# print(img2) #[4,3]
# result1 = np.dot(img1,img2)
# print(result1)
# [[175 212 13 115] img1
# [ 35 193 25 154]
# [ 77 249 212 215]]
# [[ 1 173 245] img2 175 33072 3237 54769
# [156 164 69]
# [249 12 220]
# [159 126 199]]
# [[241 73 48] result1
# [182 67 182]
# [198 79 31]]
# 1*3 + 2*1 = 5,10
# 13,22
# img3 = np.random.randint(0, 256, size=[4,4], dtype=np.uint8)
# img4 = np.random.randint(0, 256, size=[4,4], dtype=np.uint8)
# print(img3)
# print(img4)
# result2 = cv2.divide(img3,img4)
# print(result2)
# img3 = np.random.randint(0, 256, size=[4,4], dtype=np.uint8)
# img4 = np.random.randint(0, 256, size=[4,4], dtype=np.uint8)
# print(img3)
# print(img4)
# img3 =[51]
# img3 = np.array(img3)
# img4 = [144]
# img4 = np.array(img4)
# result2 = cv2.bitwise_xor(img3,img4)
# print(result2)
# [[245 51 63 187] img3 128 64 32 16 8 4 2 1
# [ 50 73 15 165] 0 0 1 1 0 0 1 1
# [ 56 129 103 97]
# [123 253 18 117]]
# [[180 144 221 151] img4 1 0 0 1 0 0 0 0
# [219 183 248 174]
# [209 84 28 174]
# [ 56 52 188 194]]
# [[180 16 29 147] result2 1 0 1 0 0 0 1 1 = 163
# [ 18 1 8 164]
# [ 16 0 4 32]
# [ 56 52 16 64]]
# img = np.random.randint(0,256,size=[4,4])
# print(img.shape) # 4*4
# img1 = np.array(img)
# print(type(img1))
# img1 = img.view(2,8) # reshape，resize, view 数组类型进行变换
# print(img1.shape)
# import cv2
# img = cv2.imread('data/my_PH2/train/masks/0.bmp',0)
# img = np.random.randint(0,10,size=(2,2),dtype=np.uint8)
# img = np.array(img)
# print(img) #(572, 765) (Y,X)
# print(img.shape)
# # cv2.imshow('img',img)
# dst = cv2.resize(img,None,fx=2,fy=2,interpolation=cv2.INTER_CUBIC)
# print(dst)
# print(dst.shape)
# dst1 = cv2.resize(img,None,fx=2,fy=2,interpolation=cv2.INTER_NEAREST)
# print(dst1)
# print(dst1.shape)
# [[3 4]
# [5 8]]
# (2, 2)
# [[3 3 3 4]
# [3 4 5 5]
# [4 5 7 7]
# [5 6 8 9]]
# (4, 4)
# [[3 3 4 4]
# [3 3 4 4]
# [5 5 8 8]
# [5 5 8 8]]
# (4, 4)
# import cv2
# img = cv2.imread('data/my_PH2/train/images/0.bmp')
# print(img.shape) #(572, 765)
# # h, w = img.shape[0:2]
# # print(img[:,:,0:1])
# img1 = img[:,:,0:1]
# print(img1.shape)