VOC数据集类别为20类, 在很多比赛中经常应用VOC数据集,一方面数据集质量比较好,一方面数据集标注比较好。缺点是数据量上不如MSCOCO数据集,这里介绍一种方法,利用python把MSCOCO数据集转换成为VOC数据集格式,分为3步,每一步为一个py文件。
import json
'''
挑选出想要的类别
'''
className = {
1: 'person',
63: 'tv',
64: 'laptop',
78: 'human face',
79: 'hair drier',
80: 'license plate',
}
# coco数据集标签的路径
coco_json_path = 'D:/FLIR/1/FLIR_ADAS_1_3.tar/FLIR_ADAS_1_3/train/thermal_annotations.json'
# 保存为新的标签(只含有想要的类别)
save_path = "COCO_train.json"
classNum = [1, 63, 64, 78, 79, 80]
def writeNum(Num):
with open(save_path, "a+") as f:
f.write(str(Num))
inputfile = []
inner = {}
# 向test.json文件写入内容
with open(coco_json_path, "r+") as f:
allData = json.load(f)
data = allData["annotations"]
print(data[1])
print("read ready")
for i in data:
if i['category_id'] in classNum:
inner = {
"filename": str(int(i["image_id"]) + 1).zfill(6), # 文件名长度为6 比如 001265
"name": className[i["category_id"]],
"bndbox": i["bbox"]
}
inputfile.append(inner)
inputfile = json.dumps(inputfile)
writeNum(inputfile)
import json
import os
nameStr = []
"""
推荐备份一下COCO数据集,方便以后使用,我这里备份了COCO数据集,
这个py文件的作用就是把COCO数据中,不想要的图片删掉,只留想要的图片。
(这里想要的图片是指step1中选的类别图片)
"""
# COCO_train.json 刚才保存的想要的类别
with open("COCO_train.json", "r+") as f:
data = json.load(f)
print("read ready")
for i in data:
imgName = "FLIR_" + str(i["filename"]) + ".jpg"
nameStr.append(imgName)
nameStr = set(nameStr)
# 你们保存的MSCOCO数据集的路径(图片文件路径)
path = "D:/FLIR/1/FLIR_ADAS_1_3.tar/FLIR_ADAS_1_3/train/train_jpg_file/"
for file in os.listdir(path):
if (file not in nameStr): os.remove(path + file)
import xml.dom
import xml.dom.minidom
import os
# from PIL import Image
import cv2
import json
'''
生成xml 文件
'''
_ANNOTATION_SAVE_PATH = 'Annotations' # 生成的xml保存的路径
_INDENT = ' ' * 4
_NEW_LINE = '\n'
_FOLDER_NODE = 'COCO2014'
_ROOT_NODE = 'annotation'
_DATABASE_NAME = 'LOGODection'
_ANNOTATION = 'COCO2014'
_AUTHOR = 'MEISI'
_SEGMENTED = '0'
_DIFFICULT = '0'
_TRUNCATED = '0'
_POSE = 'Unspecified'
def createElementNode(doc, tag, attr):
element_node = doc.createElement(tag)
text_node = doc.createTextNode(attr)
element_node.appendChild(text_node)
return element_node
def createChildNode(doc, tag, attr, parent_node):
child_node = createElementNode(doc, tag, attr)
parent_node.appendChild(child_node)
def createObjectNode(doc, attrs):
object_node = doc.createElement('object')
createChildNode(doc, 'name', attrs['name'], object_node)
createChildNode(doc, 'pose', _POSE, object_node)
createChildNode(doc, 'truncated', _TRUNCATED, object_node)
createChildNode(doc, 'difficult', _DIFFICULT, object_node)
bndbox_node = doc.createElement('bndbox')
createChildNode(doc, 'xmin', str(int(attrs['bndbox'][0])), bndbox_node)
createChildNode(doc, 'ymin', str(int(attrs['bndbox'][1])), bndbox_node)
createChildNode(doc, 'xmax', str(int(attrs['bndbox'][0] + attrs['bndbox'][2])), bndbox_node)
createChildNode(doc, 'ymax', str(int(attrs['bndbox'][1] + attrs['bndbox'][3])), bndbox_node)
object_node.appendChild(bndbox_node)
return object_node
# 将documentElement写入XML文件
def writeXMLFile(doc, filename):
tmpfile = open('tmp.xml', 'w')
doc.writexml(tmpfile, addindent=' ' * 4, newl='\n', encoding='utf-8')
tmpfile.close()
fin = open('tmp.xml')
fout = open(filename, 'w')
lines = fin.readlines()
for line in lines[1:]:
if line.split():
fout.writelines(line)
fin.close()
fout.close()
if __name__ == "__main__":
# 图片的路径
img_path = "D:/FLIR/1/FLIR_ADAS_1_3.tar/FLIR_ADAS_1_3/train/train_jpg_file/"
fileList = os.listdir(img_path)
if fileList == 0: os._exit(-1)
with open("COCO_train.json", "r") as f:
ann_data = json.load(f)
current_dirpath = os.path.dirname(os.path.abspath('__file__'))
if not os.path.exists(_ANNOTATION_SAVE_PATH):
os.mkdir(_ANNOTATION_SAVE_PATH)
for imageName in fileList:
saveName = imageName.strip(".jpg")
xml_file_name = os.path.join(_ANNOTATION_SAVE_PATH, (saveName + '.xml'))
img = cv2.imread(os.path.join(img_path, imageName))
height, width, channel = img.shape
my_dom = xml.dom.getDOMImplementation()
doc = my_dom.createDocument(None, _ROOT_NODE, None)
root_node = doc.documentElement
createChildNode(doc, 'folder', _FOLDER_NODE, root_node)
createChildNode(doc, 'filename', saveName + '.jpg', root_node)
source_node = doc.createElement('source')
createChildNode(doc, 'database', _DATABASE_NAME, source_node)
createChildNode(doc, 'annotation', _ANNOTATION, source_node)
createChildNode(doc, 'image', 'flickr', source_node)
createChildNode(doc, 'flickrid', 'NULL', source_node)
root_node.appendChild(source_node)
owner_node = doc.createElement('owner')
createChildNode(doc, 'flickrid', 'NULL', owner_node)
createChildNode(doc, 'name', _AUTHOR, owner_node)
root_node.appendChild(owner_node)
size_node = doc.createElement('size')
createChildNode(doc, 'width', str(width), size_node)
createChildNode(doc, 'height', str(height), size_node)
createChildNode(doc, 'depth', str(channel), size_node)
root_node.appendChild(size_node)
createChildNode(doc, 'segmented', _SEGMENTED, root_node)
for ann in ann_data:
"""
[5:]
"""
if (saveName == ann["filename"]):
# object节点
object_node = createObjectNode(doc, ann)
root_node.appendChild(object_node)
else:
continue
print(xml_file_name)
writeXMLFile(doc, xml_file_name)