python - 使用Python自动裁剪图像

Question

我想使用OpenCV自动将图像裁剪成许多图像，输出图像的数量是可变的。我首先用透明背景替换了白色背景。

输入图像:


我使用以下脚本将白色背景替换为透明背景:

from PIL import Image

img = Image.open('./images/SPORTS/546.png')
img = img.convert("RGBA")
datas = img.getdata()

newData = []
for item in datas:
    if item[0] == 253 and item[1] == 252 and item[2] == 252:
        newData.append((255, 255, 255, 0))
    else:
        newData.append(item)

img.putdata(newData)
img.show()
img.save("split_image_example.png", "PNG")

因此，在此示例中，我想获得4张分离的图像。

Answer 1

您可以在findContour()上使用BoundingRect()
参见http://docs.opencv.org/2.4/doc/tutorials/imgproc/shapedescriptors/bounding_rects_circles/bounding_rects_circles.html

对于您的情况:

img=cv2.imread(path_to_your_image,0)
if img is None:
    sys.exit("No input image") #good practice

#thresholding your image to keep all but the background (I took a version of your
#image with a white background, you may have to adapt the threshold
thresh=cv2.threshold(img, 250, 255, cv2.THRESH_BINARY_INV);
res=thresh[1]

#dilating the result to connect all small components in your image
kernel=cv2.getStructuringElement(cv2.MORPH_CROSS,(3,3))
for i in range(10):
    res=cv2.dilate(res,kernel)

#Finding the contours
 img2,contours,hierarchy=
cv2.findContours(res,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)


cpt=0
for contour in contours:
    #finding the bounding rectangle of your contours
    rect=cv2.boundingRect(contour)
    #cropping the image to the value of the bounding rectangle
    img2=img[rect[1]:rect[1]+rect[3],rect[0]:rect[0]+rect[2]]
    cv2.imwrite("path_you_want_to_save"+str(cpt)+".png", img2)
    cpt=cpt+1;

这是一个快速的代码，您可能需要更改:保存方法，轮廓计算参数，膨胀方法...。
最重要的是，它适合您在此处提供的图像，但可能不适用于对象离得更近或更“稀疏”的情况(如果扩展无法将它们合并在一起)