python--opencv的基本使用

python–opencv的基本使用

安装 pip install opencv-python 引用 import cv2

常用函数

读图片：

原型

Python:retval=cv.imread(filename[, flags])

image = cv2.imread(full_path_i)

imread flag参数 IMREAD_UNCHANGED Python: cv.IMREAD_UNCHANGED If set, return the loaded image as is (with alpha channel, otherwise it gets cropped). IMREAD_GRAYSCALE Python: cv.IMREAD_GRAYSCALE If set, always convert image to the single channel grayscale image (codec internal conversion). IMREAD_COLOR Python: cv.IMREAD_COLOR If set, always convert image to the 3 channel BGR color image. IMREAD_ANYDEPTH Python: cv.IMREAD_ANYDEPTH If set, return 16-bit/32-bit image when the input has the corresponding depth, otherwise convert it to 8-bit. IMREAD_ANYCOLOR Python: cv.IMREAD_ANYCOLOR If set, the image is read in any possible color format. IMREAD_LOAD_GDAL Python: cv.IMREAD_LOAD_GDAL If set, use the gdal driver for loading the image. IMREAD_REDUCED_GRAYSCALE_2 Python: cv.IMREAD_REDUCED_GRAYSCALE_2 If set, always convert image to the single channel grayscale image and the image size reduced 1/2. IMREAD_REDUCED_COLOR_2 Python: cv.IMREAD_REDUCED_COLOR_2 If set, always convert image to the 3 channel BGR color image and the image size reduced 1/2. IMREAD_REDUCED_GRAYSCALE_4 Python: cv.IMREAD_REDUCED_GRAYSCALE_4 If set, always convert image to the single channel grayscale image and the image size reduced 1/4. IMREAD_REDUCED_COLOR_4 Python: cv.IMREAD_REDUCED_COLOR_4 If set, always convert image to the 3 channel BGR color image and the image size reduced 1/4. IMREAD_REDUCED_GRAYSCALE_8 Python: cv.IMREAD_REDUCED_GRAYSCALE_8 If set, always convert image to the single channel grayscale image and the image size reduced 1/8. IMREAD_REDUCED_COLOR_8 Python: cv.IMREAD_REDUCED_COLOR_8 If set, always convert image to the 3 channel BGR color image and the image size reduced 1/8. IMREAD_IGNORE_ORIENTATION Python: cv.IMREAD_IGNORE_ORIENTATION If set, do not rotate the image according to EXIF’s orientation flag.

存照片：

Pyhton：retval=cv.imwrite(filename, img[, params])

cv2.imwrite(img_path+/out/+file_name+line_+str(line_c)+.png, image)

图片宽高：

h w:image.shape[0],image.shape[1]

图片的crop

示例代码:

x1 = int(image.shape[1]/5)
    x2 = int(image.shape[1]*4/5)
    y1 = int(image.shape[0]*3/4)
    y2 = int(image.shape[0])
    hight = int((y2 - y1)/2)
    width = x2 - x1
    crop_img= image[y1:y1+hight, x1:x1+width]

颜色转换

python: dst=cv.cvtColor(src, code[, dst[, dstCn]]) 参数: 示例代码： gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

raw域颜色转换

cv::COLOR_BayerBG2RGB = COLOR_BayerRG2BGR, //RGGB
  cv::COLOR_BayerGB2RGB = COLOR_BayerGR2BGR, //GRGB
  cv::COLOR_BayerRG2RGB = COLOR_BayerBG2BGR, //BGGR
  cv::COLOR_BayerGR2RGB = COLOR_BayerGB2BGR, //GBGR

画线

cv2.line(image, (x1, y1), (x2, y2), (255, 0, 0), 1)

canny边缘线

edges = cv2.Canny(gray, 5, 15, apertureSize=3) # apertureSize参数默认其实就是3

HoughLinesP直线检测

lines = cv2.HoughLinesP(edges, 3, np.pi / 180, 60, minLineLength=200, maxLineGap=10)
if lines is not None:
    for line in lines:
        x1, y1, x2, y2 = line[0]

Proj

png 贴图

org_img = cv2.imread(org.png) #背景
img_apple = cv2.imread(apple.png) #前景小图

rows, cols = img_apple.shape[:2]
h, w = org_img.shape[:2]
roi_org = org_img[:h, :w]
roi_targ = org_img[500:500+rows, 500:500+cols] #指定区域做融合

# 创建掩膜
img2gray = cv2.imread(apple.png,0)
ret, mask = cv2.threshold(img2gray, 10, 255, cv2.THRESH_BINARY)
mask_inv = cv2.bitwise_not(mask)
# 保留除logo外的背景
img1_bg = cv2.bitwise_and(roi_targ, roi_targ, mask=mask_inv) #腐蚀处理
img_out = cv2.add(img1_bg, img_apple)  # 进行融合
#img_out = cv2.add(img,0, img_apple,1, 1)
org_img[500:500+rows, 500:500+cols] = img_out
cv2.imwrite(out.png,org_img)