本文实例为大家分享了Python Opencv实现图片的切割处理,供大家参考,具体内容如下
Opencv对图片的切割:
方法一:
import os from PIL import Image def splitimage(src, rownum, colnum, dstpath): img = Image.open(src) w, h = img.size if rownum <= h and colnum <= w: print('Original image info: %sx%s, %s, %s' % (w, h, img.format, img.mode)) print('开始处理图片切割, 请稍候...') s = os.path.split(src) if dstpath == '': dstpath = s[0] fn = s[1].split('.') basename = fn[0] ext = fn[-1] num = 0 rowheight = h // rownum colwidth = w // colnum for r in range(rownum): for c in range(colnum): box = (c * colwidth, r * rowheight, (c + 1) * colwidth, (r + 1) * rowheight) img.crop(box).save(os.path.join(dstpath, basename + '_' + str(num) + '.' + ext), ext) num = num + 1 print('图片切割完毕,共生成 %s 张小图片。' % num) else: print('不合法的行列切割参数!') src = input('请输入图片文件路径:') if os.path.isfile(src): dstpath = input('请输入图片输出目录(不输入路径则表示使用源图片所在目录):') if (dstpath == '') or os.path.exists(dstpath): row = int(input('请输入切割行数:')) col = int(input('请输入切割列数:')) if row > 0 and col > 0: splitimage(src, row, col, dstpath) else: print('无效的行列切割参数!') else: print('图片输出目录 %s 不存在!' % dstpath) else: print('图片文件 %s 不存在!' % src)
方法二:
# coding=utf-8 import numpy as np import cv2 from PIL import Image image = cv2.imread("../staticimg/oldimg_04.jpg") b = np.array([[0,248], [512,254], [512,512],[0,512]], dtype = np.int32) c = np.array([[0,0], [512,0], [512,254],[0,248]], dtype = np.int32) roi_t = [] roi_c = [] for i in range(4): roi_t.append(b[i]) roi_c.append(c[i]) roi_t = np.asarray(roi_t) roi_t = np.expand_dims(roi_t, axis=0) im = np.zeros(image.shape[:2], dtype="uint8") cv2.polylines(im, roi_t, 1, 255) cv2.fillPoly(im, roi_t, 255) roi_c = np.asarray(roi_c) roi_c = np.expand_dims(roi_c, axis=0) imc = np.zeros(image.shape[:2], dtype="uint8") cv2.polylines(imc, roi_c, 1, 255) cv2.fillPoly(imc, roi_c, 255) mask = im maskc = imc maskedtop = cv2.bitwise_and(image,image,mask=mask) maskedbody = cv2.bitwise_and(image,image,mask=maskc) imp = Image.fromarray(image) arraytop = np.zeros((maskedtop.shape[0], maskedtop.shape[1], 4), np.uint8) arraybody = np.zeros((maskedbody.shape[0], maskedbody.shape[1], 4), np.uint8) arraytop[:, :, 0:3] = maskedtop arraybody[:, :, 0:3] = maskedbody arraytop[:, :, 3] = 0 arraytop[:,:,3][np.where(arraytop[:,:,0]>2)]=255 arraytop[:,:,3][np.where(arraytop[:,:,1]>2)]=255 arraytop[:,:,3][np.where(arraytop[:,:,2]>2)]=255 print(arraytop.max()) image_1 = Image.fromarray(arraytop) image_1.save("666.jpg","PNG") arraybody[:, :, 3] = 0 arraybody[:,:,3][np.where(arraybody[:,:,0]>2)]=255 arraybody[:,:,3][np.where(arraybody[:,:,1]>2)]=255 arraybody[:,:,3][np.where(arraybody[:,:,2]>2)]=255 print(arraybody.max()) image_2 = Image.fromarray(arraybody) image_2.save("888.jpg","PNG") # cv2.imwrite("333.jpg",maskedtop) # cv2.imwrite("222.jpg",maskedbody) # --------------------- # def cut_img(image, array_points,array_points2): # b = np.array(array_points, dtype=np.int32) # c = np.array(array_points2, dtype=np.int32) # # roi_t = [] # roi_c = [] # for i in range(2): # roi_t.append(b[i]) # roi_c.append(c[i]) # # roi_t = np.asarray(roi_t) # roi_t = np.expand_dims(roi_t, axis=0) # im = np.zeros(image.shape[:2], dtype="uint8") # cv2.polylines(im, roi_t, 1, 255) # cv2.fillPoly(im, roi_t, 255) # # roi_c = np.asarray(roi_c) # roi_c = np.expand_dims(roi_c, axis=0) # imc = np.zeros(image.shape[:2], dtype="uint8") # cv2.polylines(imc, roi_c, 1, 255) # cv2.fillPoly(imc, roi_c, 255) # mask = im # maskc = imc # kk = cv2.bitwise_and(image,image,mask=mask) # kkc = cv2.bitwise_and(image,image,mask=maskc) # cv2.imwrite("333.jpg",kk) # cv2.imwrite("222.jpg",kkc) # return cv2.bitwise_and(image, image, mask=mask)
以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持脚本之家。