制作panoptic全景分割数据集

1.用labelme标注，生成json

2.用split_train_val划分数据集，将所有img和json分别放在train，val和test文件夹中

# coding:utf-8import os
import random
import shutil'''
只需修改voc_path路径，就可以在上级目录下生成一个xml存放所有xml文件，一个JPEGImages存放所有图，和ImageSets/Main存放txt文件
'''
img_json_path = r'E:\wang\logo\image\image_json'
file_path = r'E:\wang\logo\data\logo_json_split'
image_type = ".png"train_path = os.path.join(file_path, "train")
val_path = os.path.join(file_path, "val")
test_path = os.path.join(file_path, "test")
if not os.path.exists(train_path):os.makedirs(train_path)
if not os.path.exists(val_path):os.makedirs(val_path)
if not os.path.exists(test_path):os.makedirs(test_path)trainval_percent = 0.8
train_percent = 0.9
# so test_percent = 0.1total_annotation = [f for f in os.listdir(img_json_path) if f.endswith('.json')]num = len(total_annotation)
list_index = range(num)
tv = int(num * trainval_percent)
tr = int(tv * train_percent)
trainval = random.sample(list_index, tv)
train = random.sample(trainval, tr)for i in list_index:name = total_annotation[i][:-5]print("name: ", name)img_path = img_json_path + '\\' + name + image_typejson_path = img_json_path + '\\' + name + '.json'if i in trainval:if i in train:shutil.copy(img_path, os.path.join(train_path, name + image_type))shutil.copy(json_path, os.path.join(train_path, name + '.json'))else:shutil.copy(img_path, os.path.join(val_path, name + image_type))shutil.copy(json_path, os.path.join(val_path, name + '.json'))else:shutil.copy(img_path, os.path.join(test_path, name + image_type))shutil.copy(json_path, os.path.join(test_path, name + '.json'))

3.用labelme-main\examples\instance_segmentation的labelme2coco.py生成instance_train2017.json，instance_val2017.json，instance_test2017.json

4.下载panopticapi-master并安装环境，将panoptic_coco_categories.json里面的内容修改为自己的类别，用detection2panoptic_coco_format.py将instance_train2017.json，instance_val2017.json，instance_test2017.json转换为panoptic_train2017.json，panoptic_val2017.json，panoptic_test2017.json，同时生成panoptic_train2017，panoptic_val2017，panoptic_test2017，3个mask文件夹。

至此panoptic数据集建好了

annotations里面是

panoptic_train2017里面是