直接讀取圖片
def display_img(file="p.jpeg"):
img = cv.imread(file)
print (img.shape)
cv.imshow('image',img)
cv.waitKey(0)
cv.destroyAllWindows()
讀取灰度圖片
def display_gray_img(file="p.jpeg"):
img = cv.imread(file,cv.IMREAD_GRAYSCALE)
print (img.shape)
cv.imshow('image',img)
cv.waitKey(0)
cv.destroyAllWindows()
cv.imwrite("gray_img.png",img)
讀取視頻
def display_video(file="sj.mp4"):
v = cv.VideoCapture(file)
if v.isOpened():
open,frame = v.read()
else:
open=False
while open:
ret,frame = v.read()
if frame is None:
break
if ret == True:
gray = cv.cvtColor(frame,cv.COLOR_BGR2GRAY)
cv.imshow("result",gray)
if cv.waitKey(10) 0xFF == 27:
break
v.release()
v.waitKey(0)
v.destroyAllWindows()
截取圖片
def get_frame_img(file="p.jpeg"):
img = cv.imread(file)
print (img.shape)
cat = img[0:200,0:200]
cv.imshow('get_frame_img',cat)
cv.waitKey(0)
cv.destroyAllWindows()
提取rgb通道
def extrats_rgb_img(file="p.jpeg"):
img = cv.imread(file)
b,g,r = cv.split(img)
print (b.shape,g.shape,r.shape)
new_img = cv.merge((b,g,r))
print (new_img.shape)
copy_img_r = img.copy()
copy_img_r[:,:,0]=0
copy_img_r[:,:,1]=0
cv.imshow("r_img",copy_img_r)
copy_img_g = img.copy()
copy_img_g[:,:,0]=0
copy_img_g[:,:,2]=0
cv.imshow("g_img",copy_img_g)
copy_img_b = img.copy()
copy_img_b[:,:,1]=0
copy_img_b[:,:,2]=0
cv.imshow("b_img",copy_img_b)
邊界填充
def border_fill_img(file="p.jpeg"):
border_type = [
cv.BORDER_REPLICATE,#復(fù)制法，復(fù)制邊緣
cv.BORDER_REFLECT, #反射法，對(duì)感興趣的圖像中的像素在兩邊進(jìn)行復(fù)制
cv.BORDER_REFLECT_101,#反射法，以邊緣像素為軸，對(duì)稱
cv.BORDER_WRAP,#外包裝法
cv.BORDER_CONSTANT#常量法，常量填充
]
border_title = [
"REPLICATE",
"REFLECT",
"REFLECT_101",
"WRAP",
"CONSTANT"
]
img = cv.imread(file)
top_size,bottom_size,left_size,right_size = (50,50,50,50)
plt.subplot(231)
plt.imshow(img,"gray")#原始圖像
plt.title("ORIGNAL")
for i in range(len(border_type)):
result = cv.copyMakeBorder(img,top_size,bottom_size,left_size,right_size,border_type[i])
plt.subplot(232+i)
plt.imshow(result,"gray")
plt.title(border_title[i])
plt.show()
圖像融合，變換
def img_compose(file1="tu.jpeg",file2="gui.jpeg"):
img_1 = cv.imread(file1)
img_2 = cv.imread(file2)
print (img_1.shape)
print (img_2.shape)
img_1= cv.resize(img_1,(500,500))
img_2= cv.resize(img_2,(500,500))
print (img_1.shape)
print (img_2.shape)
res = cv.addWeighted(img_1,0.4,img_2,0.6,0)
plt.imshow(res)
plt.show()
res = cv.resize(img_1,(0,0),fx=3,fy=1)
plt.imshow(res)
plt.show()
res = cv.resize(img_2,(0,0),fx=1,fy=3)
plt.imshow(res)
plt.show()
二值化處理
def Binarization(filepath):
img = cv2.imread(filepath,0)
limit = 120
ret,thresh=cv2.threshold(img,limit,255,cv2.THRESH_BINARY_INV)
plt.imshow(thresh,'gray')
plt.show()
return thresh
Binarization('t1.jpg')
到此這篇關(guān)于Python opencv操作深入詳解的文章就介紹到這了,更多相關(guān)Python opencv操作內(nèi)容請(qǐng)搜索腳本之家以前的文章或繼續(xù)瀏覽下面的相關(guān)文章希望大家以后多多支持腳本之家！
您可能感興趣的文章:- python基于OpenCV模板匹配識(shí)別圖片中的數(shù)字
- Python OpenCV高斯金字塔與拉普拉斯金字塔的實(shí)現(xiàn)
- Python OpenCV 基于圖像邊緣提取的輪廓發(fā)現(xiàn)函數(shù)
- Python+Opencv實(shí)現(xiàn)數(shù)字識(shí)別的示例代碼
- python中的opencv和PIL(pillow)轉(zhuǎn)化操作
- OpenCV+Python幾何變換的實(shí)現(xiàn)示例
- python利用opencv實(shí)現(xiàn)顏色檢測(cè)
- python+opencv實(shí)現(xiàn)車道線檢測(cè)
- python opencv實(shí)現(xiàn)圖像配準(zhǔn)與比較
- python OpenCV學(xué)習(xí)筆記
