多张图片n*m显示

小咪咪 2022-11-15 01:23 184阅读 0赞

def save_nm_img(img_row,img_putTxt,img_putTxt2):
        pic = img_row
        font = cv2.FONT_HERSHEY_PLAIN
        for i,name in enumerate(img_putTxt2): #添加名字 图片包含 了 文本信息
            cv2.putText(pic,name,(128*i,20),font,1,(255,255,255),2)   # 图片 文本， 坐标（x,y) ,字体 , 大小 颜色 粗细
        # cv2.imwrite("img.jpg", pic) #一行 所有图片
        print(pic.shape)
    
        #分成 5行10 列
        save_img = pic[0:256, 0:128 * 10]
        for i in [20,30,40,50]: #一行显示10 张图片  [y0:y1, x0:x1]。
            if pic[:,128*(i-10):].shape[1]>=1280: #hwc如果剩下的数据长度 大于10张就列拼接， 否则就丢弃，因为拼接的维度是需要一致的
                save_img = np.concatenate((save_img, pic[0:256,128*(i-10):128*i]), axis=0) #两行成拼接1列
            else:
                break
        cv2.imwrite("./sort_img_show/"+img_putTxt[0], save_img)
    
    
    def main():
        f = open(ranklist, encoding='utf-8')
        content = f.read()
        dic = json.loads(content)
    
        for idx, query_name in enumerate(list(dic.keys())[0:200]):  #排序好的底库图片
            img_row = []
            img_putTxt = []  # cv2保存图片对应添加的文本信息,图片名字
            img_putTxt2 = []  # cv2保存图片对应添加的文本信息,图片 的bgr  均值
            q = Q_ROOT + query_name
            img_q = cv2.imread(q)
            img_q = cv2.resize(img_q, (128, 256), interpolation=cv2.INTER_CUBIC)#(width, height)
            img_putTxt.append(query_name)
            # img_q = cv2.cvtColor(img_q, cv2.COLOR_RGB2GRAY)
            img_row.append(img_q)
    
            per_image_Bmean = np.mean(img_q[:, :, 0])
            per_image_Gmean = np.mean(img_q[:, :, 1])
            per_image_Rmean = np.mean(img_q[:, :, 2])
            img_putTxt2.append(str(int(np.mean(per_image_Bmean+per_image_Gmean+per_image_Rmean))))
    
            for gallery_name in dic[query_name][:50]:  #遍历底库排序好的图片名字
                g = os.path.join(G_ROOT, gallery_name)
                img_g = cv2.imread(g)
                img_g = cv2.resize(img_g, (128, 256), interpolation=cv2.INTER_CUBIC)  # (width, height)
                img_putTxt.append(gallery_name)
                # img_g = cv2.cvtColor(img_g, cv2.COLOR_RGB2GRAY)
                img_row.append(img_g)
    
                per_image_Bmean = np.mean(img_g[:, :, 0])
                per_image_Gmean = np.mean(img_g[:, :, 1])
                per_image_Rmean = np.mean(img_g[:, :, 2])
                img_putTxt2.append(str(abs(int(np.mean(per_image_Bmean+per_image_Gmean+per_image_Rmean))-int(img_putTxt2[0]))))
            # 将一张 query img  + 50张底库数据 拼接到一行
            pic = img_row[0]
            for i in range(1, len(img_row)):  # pic 会是一行所有的图片
                pic = np.concatenate((pic, img_row[i]), axis=1)
            # save_nm_img(pic,img_putTxt)
            save_nm_img(pic, img_putTxt,img_putTxt2)  #图片显示 bgr 的均值
            if idx==10:
    
                break