python opencv矩形框并切割

本博不具有普适性。

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https://blog.csdn.net/loovelj/article/details/78739790

https://blog.csdn.net/wsp_1138886114/article/details/82945328

pencv阈值

https://blog.csdn.net/a19990412/article/details/81172426

https://blog.csdn.net/jianyuchen23/article/details/80835352

先看这两篇博客找理论，然后我这边直接上我的代码，该代码可对路径下的图片批量操作，矩形切割

import cv2
import os

def get_imgs(imagePath):
    imageFilenames = []
    labels = []
    categoryList = [None]
    categoryList = [c for c in sorted(os.listdir(imagePath))
                    if c[0] != '.' and
                    os.path.isdir(os.path.join(imagePath, c))] 
   
    for category in categoryList:
        if category:
            walkPath = os.path.join(imagePath, category)
        else:
            walkPath = imagePath
            category = os.path.split(imagePath)[1]

        w = _walk(walkPath)
        while True:
            try:
                # dirpath = new_data_manual/train/ce
                dirpath, dirnames, filenames = w.__next__()
            except StopIteration:
                break
            # Don't enter directories that begin with '.'
            for d in dirnames[:]:
                if d.startswith('.'):
                    dirnames.remove(d)
            dirnames.sort()
            
            # Ignore files that begin with 'ori'
            filenames = [f for f in filenames if not f.startswith('ori')]
            filenames.sort()
            # imageFilenames = [os.path.join(dirpath, f) for f in filenames]

            for f in filenames:
                imageFilenames.append([category, os.path.join(dirpath, f)])
    # ['label',img_path]
    return imageFilenames
                
def _walk(top):
    """
    Directory tree generator lifted from python 2.6 and then
    stripped down.  It improves on the 2.5 os.walk() by adding
    the 'followlinks' capability.
    GLU: copied from image sensor
    """
    names = os.listdir(top)
    dirs, nondirs = [], []
    for name in names:
        if os.path.isdir(os.path.join(top, name)):
            dirs.append(name)
        else:
            nondirs.append(name)

    yield top, dirs, nondirs
    
    for name in dirs:
        path = os.path.join(top, name)
        for x in _walk(path):
            yield x
    
    
all_image_path = 'data'
new_all_image_path = 'new_data'

data = get_imgs(all_image_path) 
print(data)
labels,source_files=zip(*data)
 

#import pdb
#pdb.set_trace()
for i in range(0,len(data)):
    initial_img = cv2.imread(source_files[i])
    gray = cv2.cvtColor(initial_img, cv2.COLOR_BGR2GRAY)
    #this value is important , don't change it !!!
    filepath,tempfilename = os.path.split(source_files[i])
    _,lab = os.path.split(filepath)
    if lab =='':
        thresh=0
    else:
        thresh=50
        
    ret,binary = cv2.threshold(gray, thresh, 255, cv2.THRESH_BINARY)
    _,contours, hierarchy = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    #print ("contours:类型：",type(contours))
    #print ("第0 个contours:",type(contours[0]))
    #print ("contours 数量：",len(contours))
    #print ("contours[0]点的个数：",len(contours[0]))
    #print ("contours[1]点的个数：",len(contours[1]))
    #for i in range(0,len(contours)):  
        #x, y, w, h = cv2.boundingRect(contours[i])   
        #cv2.rectangle(img, (x,y), (x+w,y+h), (153,153,0), 5) 
    
 
    x, y, w, h = cv2.boundingRect(contours[len(contours)-1])   
    #cv2.rectangle(initial_img, (x,y), (x+w,y+h), (153,153,0), 5)
    crop_image = initial_img[y+2:y+h-2,x+2:x+w-2]

    
    #cv2.imwrite("1.jpg",initial_img)

    
    tmp_target_file = new_all_image_path+'/'+labels[i]+'/'+lab+'/' 
    filepath,tempfilename = os.path.split(source_files[i])
    filename,extension = os.path.splitext(tempfilename)
    print(tmp_target_file+filename+".jpg")    
    cv2.imwrite(tmp_target_file+filename+".jpg",crop_image)