OpenCV-python一般的な使い方・個人的なまとめ

今日はpython openCVの一般的な使い方をまとめてみました.
含む
    1. 原図を表示
    2. 階調図を表示
    3. GRBチャネル分離
    4. 座標の回転
    5. サイズの再定義
    6. 画像の切り取り
    7. 輝度の向上
    8. ヒストグラム等化
    9. フィルタリング
    10. エッジ検出
    11. かくてんけんしゅつ

#coding: utf-8
import cv2
import numpy as np

#    
im = cv2.imread("star.jpg")
cv2.imshow("pic.jpg", im)
cv2.waitKey(0)

#     
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
cv2.imshow("gray.jpg", gray)
cv2.waitKey(0)

#BGR    
(B, G, R) = cv2.split(im)
cv2.imshow("Red", R)
cv2.imshow("Green", G)
cv2.imshow("Blue", B)
cv2.waitKey(0)

#    
rows, cols, channel = im.shape
M = cv2.getRotationMatrix2D(((cols-1)/2.0, (rows-1)/2.0), 90, 1)
dst = cv2.warpAffine(im, M, (cols, rows))
cv2.imshow("dst", dst)
dst = cv2.flip(im, 1)   #    
dst = cv2.flip(im, 0)   #    
dst = cv2.flip(im, -1)  #      
cv2.waitKey(0)

#resize
res = cv2.resize(im, None, fx=2, fy=0.5, interpolation = cv2.INTER_CUBIC)
cv2.imshow("res", res)
cv2.waitKey(0)

#    
im1 = im[200:500, 300:600]  #(y0:y1, x0:x1)
cv2.imshow("im1", im1)
cv2.waitKey(0)

#    
res1 = np.uint8(np.clip(1.5*im,0,255))
res2 = np.uint8(np.clip(0.7*im,0,255))
tmp1 = np.hstack((im, res1, res2))
cv2.imshow("image", tmp1)
cv2.waitKey(0)

#       、   、    
#     
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
equalize = cv2.equalizeHist(gray)
cv2.imshow('equalize', equalize)
cv2.waitKey(0)

#  
blur = cv2.blur(im, (5,5))                      #      
gauss = cv2.GaussianBlur(im, (5,5), 0)          #    
median = cv2.medianBlur(im, 5)                  #    
bilateral = cv2.bilateralFilter(im, 9, 5, 5)    #    
filt = np.hstack([blur, gauss, median, bilateral])
cv2.imshow("filter", filt)
cv2.waitKey(0)

#    
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
_, binary = cv2.threshold(gray,127,255,cv2.THRESH_BINARY)
contours, hierarchy = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
con = cv2.drawContours(im,contours,-1,(0,0,255),3)
cv2.imshow("con", con)
cv2.waitKey(0)

#    
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
dst = cv2.cornerHarris(gray,5,5,0.04)
dst = cv2.dilate(dst,None)#    
im[dst>0.01*dst.max()]=[0,0,255]
cv2.imshow('dst',im)
cv2.waitKey(0)
cv2.destroyAllWindows()