1.python提取COCO数据集中特定的类
安装pycocotools github地址：https://github.com/philferriere/cocoapi
pip install git https://github.com/philferriere/cocoapi.git#subdirectory=PythonAPI
提取特定的类别如下：
代码语言：javascript复制from pycocotools.coco import COCO
import os
import shutil
from tqdm import tqdm
import skimage.io as io
import matplotlib.pyplot as plt
import cv2
from PIL import Image, ImageDraw
#the path you want to save your results for coco to voc
savepath="/media/huanglong/Newsmy/COCO/" #保存提取类的路径,我放在同一路径下
img_dir=savepath 'images/'
anno_dir=savepath 'Annotations/'
# datasets_list=['train2014', 'val2014']
datasets_list=['train2014']
classes_names = ['person'] #coco有80类，这里写要提取类的名字，以person为例
#Store annotations and train2014/val2014/... in this folder
dataDir= '/media/huanglong/Newsmy/COCO/' #原coco数据集
headstr = """
<annotation
<folder VOC</folder
<filename %s</filename
<source
<database My Database</database
<annotation COCO</annotation
<image flickr</image
<flickrid NULL</flickrid
</source
<owner
<flickrid NULL</flickrid
<name company</name
</owner
<size
<width %d</width
<height %d</height
<depth %d</depth
</size
<segmented 0</segmented
"""
objstr = """
<object
<name %s</name
<pose Unspecified</pose
<truncated 0</truncated
<difficult 0</difficult
<bndbox
<xmin %d</xmin
<ymin %d</ymin
<xmax %d</xmax
<ymax %d</ymax
</bndbox
</object
"""
tailstr = '''
</annotation
'''
#if the dir is not exists,make it,else delete it
def mkr(path):
if os.path.exists(path):
shutil.rmtree(path)
os.mkdir(path)
else:
os.mkdir(path)
mkr(img_dir)
mkr(anno_dir)
def id2name(coco):
classes=dict()
for cls in coco.dataset['categories']:
classes[cls['id']]=cls['name']
return classes
def write_xml(anno_path,head, objs, tail):
f = open(anno_path, "w")
f.write(head)
for obj in objs:
f.write(objstr%(obj[0],obj[1],obj[2],obj[3],obj[4]))
f.write(tail)
def save_annotations_and_imgs(coco,dataset,filename,objs):
#eg:COCO_train2014_000000196610.jpg-- COCO_train2014_000000196610.xml
anno_path=anno_dir filename[:-3] 'xml'
img_path=dataDir dataset '/' filename
print(img_path)
dst_imgpath=img_dir filename
img=cv2.imread(img_path)
#if (img.shape[2] == 1):
# print(filename " not a RGB image")
# return
shutil.copy(img_path, dst_imgpath)
head=headstr % (filename, img.shape[1], img.shape[0], img.shape[2])
tail = tailstr
write_xml(anno_path,head, objs, tail)
def showimg(coco,dataset,img,classes,cls_id,show=True):
global dataDir
I=Image.open('%s/%s/%s'%(dataDir,dataset,img['file_name']))
#通过id，得到注释的信息
annIds = coco.getAnnIds(imgIds=img['id'], catIds=cls_id, iscrowd=None)
# print(annIds)
anns = coco.loadAnns(annIds)
# print(anns)
# coco.showAnns(anns)
objs = []
for ann in anns:
class_name=classes[ann['category_id']]
if class_name in classes_names:
print(class_name)
if 'bbox' in ann:
bbox=ann['bbox']
xmin = int(bbox[0])
ymin = int(bbox[1])
xmax = int(bbox[2] bbox[0])
ymax = int(bbox[3] bbox[1])
obj = [class_name, xmin, ymin, xmax, ymax]
objs.append(obj)
draw = ImageDraw.Draw(I)
draw.rectangle([xmin, ymin, xmax, ymax])
if show:
plt.figure()
plt.axis('off')
plt.imshow(I)
plt.show()
return objs
for dataset in datasets_list:
#./COCO/annotations/instances_train2014.json
annFile='{}/annotations/instances_{}.json'.format(dataDir,dataset)
#COCO API for initializing annotated data
coco = COCO(annFile)
#show all classes in coco
classes = id2name(coco)
print(classes)
#[1, 2, 3, 4, 6, 8]
classes_ids = coco.getCatIds(catNms=classes_names)
print(classes_ids)
for cls in classes_names:
#Get ID number of this class
cls_id=coco.getCatIds(catNms=[cls])
img_ids=coco.getImgIds(catIds=cls_id)
print(cls,len(img_ids))
# imgIds=img_ids[0:10]
for imgId in tqdm(img_ids):
img = coco.loadImgs(imgId)[0]
filename = img['file_name']
# print(filename)
objs=showimg(coco, dataset, img, classes,classes_ids,show=False)
print(objs)
save_annotations_and_imgs(coco, dataset, filename, objs)2. 将上一步提取的COCO 某一类 xml转为COCO标准的json文件：
代码语言：javascript复制# -*- coding: utf-8 -*-
# @Time : 2019/8/27 10：48
# @Author :Rock
# @File : voc2coco.py
# just for object detection
import xml.etree.ElementTree as ET
import os
import json
coco = dict()
coco['images'] = []
coco['type'] = 'instances'
coco['annotations'] = []
coco['categories'] = []
category_set = dict()
image_set = set()
category_item_id = 0
image_id = 0
annotation_id = 0
def addCatItem(name):
global category_item_id
category_item = dict()
category_item['supercategory'] = 'none'
category_item_id = 1
category_item['id'] = category_item_id
category_item['name'] = name
coco['categories'].append(category_item)
category_set[name] = category_item_id
return category_item_id
def addImgItem(file_name, size):
global image_id
if file_name is None:
raise Exception('Could not find filename tag in xml file.')
if size['width'] is None:
raise Exception('Could not find width tag in xml file.')
if size['height'] is None:
raise Exception('Could not find height tag in xml file.')
img_id = "d" % image_id
image_id = 1
image_item = dict()
image_item['id'] = int(img_id)
# image_item['id'] = image_id
image_item['file_name'] = file_name
image_item['width'] = size['width']
image_item['height'] = size['height']
coco['images'].append(image_item)
image_set.add(file_name)
return image_id
def addAnnoItem(object_name, image_id, category_id, bbox):
global annotation_id
annotation_item = dict()
annotation_item['segmentation'] = []
seg = []
# bbox[] is x,y,w,h
# left_top
seg.append(bbox[0])
seg.append(bbox[1])
# left_bottom
seg.append(bbox[0])
seg.append(bbox[1] bbox[3])
# right_bottom
seg.append(bbox[0] bbox[2])
seg.append(bbox[1] bbox[3])
# right_top
seg.append(bbox[0] bbox[2])
seg.append(bbox[1])
annotation_item['segmentation'].append(seg)
annotation_item['area'] = bbox[2] * bbox[3]
annotation_item['iscrowd'] = 0
annotation_item['ignore'] = 0
annotation_item['image_id'] = image_id
annotation_item['bbox'] = bbox
annotation_item['category_id'] = category_id
annotation_id = 1
annotation_item['id'] = annotation_id
coco['annotations'].append(annotation_item)
def parseXmlFiles(xml_path):
for f in os.listdir(xml_path):
if not f.endswith('.xml'):
continue
bndbox = dict()
size = dict()
current_image_id = None
current_category_id = None
file_name = None
size['width'] = None
size['height'] = None
size['depth'] = None
xml_file = os.path.join(xml_path, f)
# print(xml_file)
tree = ET.parse(xml_file)
root = tree.getroot()
if root.tag != 'annotation':
raise Exception('pascal voc xml root element should be annotation, rather than {}'.format(root.tag))
# elem is <folder , <filename , <size , <object
for elem in root:
current_parent = elem.tag
current_sub = None
object_name = None
if elem.tag == 'folder':
continue
if elem.tag == 'filename':
file_name = elem.text
if file_name in category_set:
raise Exception('file_name duplicated')
# add img item only after parse <size tag
elif current_image_id is None and file_name is not None and size['width'] is not None:
if file_name not in image_set:
current_image_id = addImgItem(file_name, size)
# print('add image with {} and {}'.format(file_name, size))
else:
raise Exception('duplicated image: {}'.format(file_name))
# subelem is <width , <height , <depth , <name , <bndbox
for subelem in elem:
bndbox['xmin'] = None
bndbox['xmax'] = None
bndbox['ymin'] = None
bndbox['ymax'] = None
current_sub = subelem.tag
if current_parent == 'object' and subelem.tag == 'name':
object_name = subelem.text
if object_name not in category_set:
current_category_id = addCatItem(object_name)
else:
current_category_id = category_set[object_name]
elif current_parent == 'size':
if size[subelem.tag] is not None:
raise Exception('xml structure broken at size tag.')
size[subelem.tag] = int(subelem.text)
# option is <xmin , <ymin , <xmax , <ymax , when subelem is <bndbox
for option in subelem:
if current_sub == 'bndbox':
if bndbox[option.tag] is not None:
raise Exception('xml structure corrupted at bndbox tag.')
bndbox[option.tag] = int(option.text)
# only after parse the <object tag
if bndbox['xmin'] is not None:
if object_name is None:
raise Exception('xml structure broken at bndbox tag')
if current_image_id is None:
raise Exception('xml structure broken at bndbox tag')
if current_category_id is None:
raise Exception('xml structure broken at bndbox tag')
bbox = []
# x
bbox.append(bndbox['xmin'])
# y
bbox.append(bndbox['ymin'])
# w
bbox.append(bndbox['xmax'] - bndbox['xmin'])
# h
bbox.append(bndbox['ymax'] - bndbox['ymin'])
# print('add annotation with {},{},{},{}'.format(object_name, current_image_id, current_category_id,
# bbox))
addAnnoItem(object_name, current_image_id, current_category_id, bbox)
if __name__ == '__main__':
#修改这里的两个地址，一个是xml文件的父目录；一个是生成的json文件的绝对路径
xml_path = r'G:datasetCOCOpersoncoco_val2014annotations\'
json_file = r'G:datasetCOCOpersoncoco_val2014instances_val2014.json'
parseXmlFiles(xml_path)
json.dump(coco, open(json_file, 'w'))3.python提取Pascal Voc数据集中特定的类
代码语言：javascript复制# -*- coding: utf-8 -*-
# @Function:There are 20 classes in VOC data set. If you need to extract specific classes, you can use this program to extract them.
import os
import shutil
ann_filepath='E:/VOCdevkit/VOC2012/Annotations/'
img_filepath='E:/VOCdevkit/VOC2012/JPEGImages/'
img_savepath='E:TrafficDatasets/JPEGImages/'
ann_savepath='E:TrafficDatasets/Annotations/'
if not os.path.exists(img_savepath):
os.mkdir(img_savepath)
if not os.path.exists(ann_savepath):
os.mkdir(ann_savepath)
names = locals()
classes = ['aeroplane','bicycle','bird', 'boat', 'bottle',
'bus', 'car', 'cat', 'chair', 'cow','diningtable',
'dog', 'horse', 'motorbike', 'pottedplant',
'sheep', 'sofa', 'train', 'tvmonitor', 'person']
for file in os.listdir(ann_filepath):
print(file)
fp = open(ann_filepath '\' file) #打开Annotations文件
ann_savefile=ann_savepath file
fp_w = open(ann_savefile, 'w')
lines = fp.readlines()
ind_start = []
ind_end = []
lines_id_start = lines[:]
lines_id_end = lines[:]
classes1 = 'tt<name bicycle</name n'
classes2 = 'tt<name bus</name n'
classes3 = 'tt<name car</name n'
classes4 = 'tt<name motorbike</name n'
classes5 = 'tt<name train</name n'
#在xml中找到object块，并将其记录下来
while "t<object n" in lines_id_start:
a = lines_id_start.index("t<object n")
ind_start.append(a) #ind_start是<object 的行数
lines_id_start[a] = "delete"
while "t</object n" in lines_id_end:
b = lines_id_end.index("t</object n")
ind_end.append(b) #ind_end是</object 的行数
lines_id_end[b] = "delete"
#names中存放所有的object块
i = 0
for k in range(0, len(ind_start)):
names['block%d' % k] = []
for j in range(0, len(classes)):
if classes[j] in lines[ind_start[i] 1]:
a = ind_start[i]
for o in range(ind_end[i] - ind_start[i] 1):
names['block%d' % k].append(lines[a o])
break
i = 1
#print(names['block%d' % k])
#xml头
string_start = lines[0:ind_start[0]]
#xml尾
if((file[2:4]=='09') | (file[2:4]=='10') | (file[2:4]=='11')):
string_end = lines[(len(lines) - 11):(len(lines))]
else:
string_end = [lines[len(lines) - 1]]
#在给定的类中搜索，若存在则，写入object块信息
a = 0
for k in range(0, len(ind_start)):
if classes1 in names['block%d' % k]:
a = 1
string_start = names['block%d' % k]
if classes2 in names['block%d' % k]:
a = 1
string_start = names['block%d' % k]
if classes3 in names['block%d' % k]:
a = 1
string_start = names['block%d' % k]
if classes4 in names['block%d' % k]:
a = 1
string_start = names['block%d' % k]
if classes5 in names['block%d' % k]:
a = 1
string_start = names['block%d' % k]
string_start = string_end
# print(string_start)
for c in range(0, len(string_start)):
fp_w.write(string_start[c])
fp_w.close()
#如果没有我们寻找的模块，则删除此xml，有的话拷贝图片
if a == 0:
os.remove(ann_savepath file)
else:
name_img = img_filepath os.path.splitext(file)[0] ".jpg"
shutil.copy(name_img, img_savepath)
fp.close()以上这篇python实现提取COCO,VOC数据集中特定的类就是小编分享给大家的全部内容了，希望能给大家一个参考。
