資料集的具體介紹就看官方網址就行，如何利用這個資料集做目標檢測呢？就是要把畫素的例項級分割轉為包圍框xmin,xmax,ymin,ymax即可。以處理road_04為例，程式碼展示如何使用。

import json import os   from os import listdir, getcwd from os.path import join import os.path rootdir='/home/wang/下載/資料集/apolloscape/Image/road04_ins'　＃影象資料夾絕對地址 def position(pos):     x=[]     y=[]     nums=len(pos)     for i in range(nums):         x.append(pos[i][0])         y.append(pos[i][1])     x_max=max(x)     x_min=min(x)     y_max=max(y)     y_min=min(y)     b=(float(x_min),float(x_max),float(y_min),float(y_max))     #b=(x_min,x_max,y_min,y_max)     return b   def convert(size, box):     dw = 1./(size[0])     dh = 1./(size[1])     x = (box[0] + box[1])/2.0 - 1     y = (box[2] + box[3])/2.0 - 1     w = box[1] - box[0]     h = box[3] - box[2]     x = x*dw     w = w*dw     y = y*dh     h = h*dh     return (x,y,w,h)   def convert_annotation(image_id):     load_f=open("./label/road04_ins/%s.json"%(image_id),'r')　＃標籤資料夾相對地址     load_dict = json.load(load_f)     out_file = open('./voc_type/road04_ins/%s.txt'%(image_id), 'w')　＃輸出標籤存放地址     #keys=tuple(load_dict.keys())       w=load_dict['imgWidth']     h=load_dict['imgHeight']     #print(h)     objects=load_dict['objects']     nums=len(objects)     #print(nums)     #object_key=tuple(objects.keys()                      for i in range(0,nums):         labels=objects[i]['label']         #print(i)         if (str(labels) in ['36','37']):             #print(labels)             pos=objects[i]['polygons'][0]                 b=position(pos)             bb = convert((w,h), b)             cls_id=2             out_file.write(str(cls_id) + " " + " ".join([str(a) for a in bb]) + '\n')             #print(type(pos))         elif (str(labels) in['33','38','39','40']):             #print(labels)             pos=objects[i]['polygons'][0]             b=position(pos)             bb = convert((w,h), b)             cls_id=1             out_file.write(str(cls_id) + " " + " ".join([str(a) for a in bb]) + '\n')   def image_id(rootdir):     a=[]     for parent,dirnames,filenames in os.walk(rootdir):         for filename in filenames:             filename=filename.strip('.jpg')             #print(filename)             a.append(filename)     return a names=image_id(rootdir) for image_id in names:     convert_annotation(image_id)

發現圖片比標籤多時，就用做差刪除無標籤圖片：

#encoding:utf-8 import os import os.path from os import listdir, getcwd from os.path import join txt_dir='./label/road04_ins'   pic_dir='./Image/road04_ins'

def txt(rootdir):     a=[]     for parent,dirnames,filenames in os.walk(rootdir):         for filenames in filenames:             filenames=filenames.strip('.json')             a.append(filenames)     return a def pic(rootdir):     b=[]     for parent,dirnames,filenames in os.walk(rootdir):         for filenames in filenames:             filenames=filenames.strip('.jpg')             b.append(filenames)     return b

txt_set=txt(txt_dir) txt_set=set(txt_set) pic_set=pic(pic_dir) pic_set=set(pic_set) #comp=txt_set-pic_set comp=pic_set-txt_set print("ok") print(len(comp))

for item in comp:     file=pic_dir+'/'+item+'.jpg'     if os.path.exists(file):         os.remove(file)         print(file)          #for item in comp:  #   file=txt_dir+'/'+item+'.json'   #  if os.path.exists(file):    #     os.remove(file)     #    print(file)