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案例一:
import cv2 import numpy as np import os import glob # img1=cv2.imread(r"F:\myyolov5\202302141303-L2_27.jpg") # print(img1.shape) # img2=cv2.imread(r"F:\myyolov5\202303011344R2_112_1.jpg") # print(img2.shape) # img1=cv2.resize(img1,(512,500)) # img2=cv2.resize(img2,(512,500)) # inputs=np.hstack((img1,img2)) # # cv2.imshow("input img",inputs) # cv2.imwrite(r"F:\Desktop\a.jpg",inputs) # cv2.waitKey(0) def open_image(path1): img_path = glob.glob(path1) print(img_path) return np.array([cv2.imread(true_path,0) for true_path in img_path]) def combine_images(datasets,newraw,newcol): raw,col = datasets[0].shape newimage = np.zeros((newraw*raw,newcol*col)) for i in range(0,newraw): for j in range(0,newcol): for ii in range(0,raw): for jj in range(0,col): newimage[i*raw+ii][j*col+jj] = output[i*newcol+j][ii][jj] return newimage if __name__ == '__main__': inputpath = 'F:\Desktop\myfile\*' output = open_image(inputpath) ohhh = combine_images(output,1,14) # 这个4,6的意思就是,我的图片通过那个打开的函数之后,变成了一个大的ndarray里面有24张图片,我想让他们以,行4列6,的形式组合起来。 cv2.imwrite(r"F:\Desktop\b.jpg",ohhh)
案例二:
def image_resize(img_name): img=cv2.imread(img_name,0) # w,h=img.shape # img=cv2.resize(img,(int(w/2),int(h/2))) return img def open_image(path1): img_path = glob.glob(path1) print(img_path) img_path.sort(key=lambda x: int(x.split("\\")[-1].split(".")[0])) print(img_path) # return np.array([cv2.imread(true_path,0) for true_path in img_path]) return np.array([image_resize(true_path) for true_path in img_path]) def combine_images(datasets,newraw,newcol): raw,col = datasets[0].shape newimage = np.zeros((newraw*raw,newcol*col)) for i in range(0,newraw): for j in range(0,newcol): for ii in range(0,raw): for jj in range(0,col): newimage[i*raw+ii][j*col+jj] = output[i*newcol+j][ii][jj] return newimage if __name__ == '__main__': num_name="right_up" select="right_up" # inputpath = r'F:\Desktop\image\right_up\352\*' inputpath=r"D:\image\%s\%s\*"%(select,num_name) outputpath=r"D:\360_ditie_concat_after_image1\%s"%(select) if not os.path.exists(outputpath): os.mkdir(outputpath) # print(inputpath) output = open_image(inputpath) print(output.shape) ohhh=np.concatenate(output,1) print(ohhh.shape) # ohhh = combine_images(output,1,output.shape[0]) # 这个4,6的意思就是,我的图片通过那个打开的函数之后,变成了一个大的ndarray里面有24张图片,我想让他们以,行4列6,的形式组合起来。 # print(ohhh.shape) # cv2.imwrite(os.path.join(outputpath,"GZDT18-043044_left_up_camImg_%s.jpg"%(num_name)),ohhh,[cv2.IMWRITE_JPEG_QUALITY, 90]) cv2.imwrite(os.path.join(outputpath, "GZDT18-043044_%s_camImg_%s.png" % (select,num_name)), ohhh)
案例三:
import cv2 import numpy as np import os import glob def open_image(path1): img_path = glob.glob(path1) print(img_path) img_path.sort(key=lambda x: int(x.split("\\")[-1].split(".")[0])) print(img_path) x1,x2,x3,x4=img_path[:15],img_path[15:30],img_path[30:45],img_path[45:60] x1=np.array([cv2.imread(true_path, 0) for true_path in x1]) x2=np.array([cv2.imread(true_path,0) for true_path in x2]) x3=np.array([cv2.imread(true_path,0) for true_path in x3]) x4=np.array([cv2.imread(true_path,0) for true_path in x4]) return x1,x2,x3,x4 def combine_images(datasets,newraw,newcol): raw,col = datasets[0].shape newimage = np.zeros((newraw*raw,newcol*col)) for i in range(0,newraw): for j in range(0,newcol): for ii in range(0,raw): for jj in range(0,col): newimage[i*raw+ii][j*col+jj] = output[i*newcol+j][ii][jj] return newimage if __name__ == '__main__': inputpath = r'F:\Desktop\my_gaotietu\*' print(inputpath) # inputpath=inputpath.sort(key=lambda x: int(x.split('/')[-1].split('.')[0].split('_')[-1])) # print(inputpath) output = open_image(inputpath) ohhh = combine_images(output[0],1,15) # 这个4,6的意思就是,我的图片通过那个打开的函数之后,变成了一个大的ndarray里面有24张图片,我想让他们以,行4列6,的形式组合起来。 cv2.imwrite(r"F:\Desktop\my_gantie_save\1.jpg",ohhh) ohhh_1 = combine_images(output[1], 1, 15) cv2.imwrite(r"F:\Desktop\my_gantie_save\2.jpg", ohhh_1) ohhh_2 = combine_images(output[2], 1, 15) cv2.imwrite(r"F:\Desktop\my_gantie_save\3.jpg", ohhh_2) ohhh_3 = combine_images(output[3], 1, 15) cv2.imwrite(r"F:\Desktop\my_gantie_save\4.jpg", ohhh_3)
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