opencv-python的一些简单用法

# coding=utf-8
import numpy as np
import cv2
import cv2.cv as cv
import skimage
cat_root = '/home/hjxu/PycharmProjects/opencv2_experiment/cat.jpg'
hjxu = '/home/hjxu/PycharmProjects/HMM_face/xuhaijun.JPG'
img = cv2.imread(cat_root)
from skimage import measure,morphology
'''#========opencv中的load函数=======
image = cv.LoadImage('/home/hjxu/PycharmProjects/opencv2_experiment/cat.jpg')
cv.NamedWindow('a_window', cv.CV_WINDOW_AUTOSIZE) #Facultative
cv.ShowImage('a_window', image) #Show the image
cv.WaitKey(0)
#=========================
'''

'''
# ======加载固定的mode
grayImage = cv2.imread(cat_root, cv2.CV_LOAD_IMAGE_GRAYSCALE)
# 可选参数CV_LOAD_IMAGE_COLOR (BGR), CV_LOAD_IMAGE_GRAYSCALE (grayscale), CV_LOAD_IMAGE_UNCHANGED(neither)
cv2.imshow('img-cat',grayImage)
# cv2.imwrite('MyPicGray.png', grayImage)
cv.WaitKey(0)
# ====加载固定的mode
'''

'''
#======获取图片的属性
img = cv2.imread(cat_root)
print img.shape
# (360, 480, 3)
print img.size
# 518400
print img.dtype
# uint8
# 在debug的时候，dtype很重要
# 获取图片的属性==========
'''

'''
# ========得到灰度图
img = cv2.imread(hjxu)
GrayImage=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
cv2.imshow('img-cat',GrayImage)
cv.WaitKey(0)
cv2.destroyAllWindows()
# ========得到灰度图
'''

'''
# ============OStu阈值法
img = cv2.imread(cat_root)
GrayImage=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) #直接读取灰度图像
retval, dst = cv2.threshold(GrayImage, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
print retval #retval是阈值
# retval, dst2 = cv2.threshold(GrayImage, 100, 255, cv2.THRESH_BINARY)
retval, dst3 = cv2.threshold(GrayImage,0,255,cv2.THRESH_BINARY_INV)
retval, dst1 = cv2.threshold(GrayImage, 0, 255, cv2.THRESH_OTSU)
cv2.imshow('img-cat',dst)
cv2.imshow('img-cat2',dst1)
cv2.imshow('img-cat3',dst3)
cv.WaitKey(0)
cv2.destroyAllWindows()
# ============OStu阈值法
'''

'''
emptyImage = np.zeros(img.shape, np.uint8)

emptyImage2 = img.copy()

emptyImage3 = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# emptyImage3[...]=0

cv2.imshow("EmptyImage", emptyImage)
cv2.imshow("Image", img)
cv2.imshow("EmptyImage2", emptyImage2)
cv2.imshow("EmptyImage3", emptyImage3)
cv2.imwrite("./cat2.jpg", img, [int(cv2.IMWRITE_JPEG_QUALITY), 5])
cv2.imwrite("./cat3.jpg", img, [int(cv2.IMWRITE_JPEG_QUALITY), 100])
cv2.imwrite("./cat.png", img, [int(cv2.IMWRITE_PNG_COMPRESSION), 0])
cv2.imwrite("./cat2.png", img, [int(cv2.IMWRITE_PNG_COMPRESSION), 9])
cv2.waitKey(0)
cv2.destroyAllWindows()
'''

'''
img = cv2.imread(cat_root)
GrayImage=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) #直接读取灰度图像
retval, dst = cv2.threshold(GrayImage, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
print retval
dst1 = morphology.remove_small_objects(dst,2000,connectivity=1)
bbox=measure.regionprops(dst1)[0]['bbox']

cv2.imshow('img-cat',dst)
cv2.imshow('img-cat1',dst1)
cv.WaitKey(0)
cv2.destroyAllWindows()
'''

# img1 = np.array(img)
# img_tmp=skimage.img_as_float(img1).astype(np.float32)
print('has done...')
#import cv2   # //导入opencv模块
c=cv2.VideoCapture(0)  #  //初始化摄像头
img=c.read()  #  //获取摄像头内容
cv2.imwrite("photo.png",img[1])  #  //将获取的内容写到文件
True  #  //写出成功