vbb转xml
主要是针对Caltech数据库中vbb格式的标注文件，转化为xml格式的工具。
#-*- coding:utf-8 -*-
import os, glob
import cv2
from scipy.io import loadmat
from collections import defaultdict
import numpy as np
from lxml import etree, objectify
def vbb_anno2dict(vbb_file, cam_id):
#通过os.path.basename获得路径的最后部分“文件名.扩展名”
#通过os.path.splitext获得文件名
filename = os.path.splitext(os.path.basename(vbb_file))[0]
#定义字典对象annos
annos = defaultdict(dict)
vbb = loadmat(vbb_file)
# object info in each frame: id, pos, occlusion, lock, posv
objLists = vbb['A'][0][0][1][0]
objLbl = [str(v[0]) for v in vbb['A'][0][0][4][0]] #可查看所有类别
# person index
person_index_list = np.where(np.array(objLbl) == "person")[0] #只选取类别为‘person’的xml
print("jyye-----------")
for frame_id, obj in enumerate(objLists):
if len(obj) > 0:
frame_name = str(cam_id) + "_" + str(filename) + "_" + str(frame_id+1) + ".jpg"
annos[frame_name] = defaultdict(list)
annos[frame_name]["id"] = frame_name
annos[frame_name]["label"] = "PEOPLE" ###"person"
for id, pos, occl in zip(obj['id'][0], obj['pos'][0], obj['occl'][0]):
id = int(id[0][0]) - 1 # for matlab start from 1 not 0
if not id in person_index_list: # only use bbox whose label is person
continue
pos = pos[0].tolist()
occl = int(occl[0][0])
annos[frame_name]["occlusion"].append(occl)
annos[frame_name]["bbox"].append(pos)
if not annos[frame_name]["bbox"]:
del annos[frame_name]
#print (annos)
return annos
def seq2img(annos, seq_file, outdir, cam_id):
cap = cv2.VideoCapture(seq_file)
index = 1
# captured frame list
v_id = os.path.splitext(os.path.basename(seq_file))[0]
cap_frames_index = np.sort([int(os.path.splitext(id)[0].split("_")[2]) for id in annos.keys()])
while True:
ret, frame = cap.read()
print (ret)
if ret:
if not index in cap_frames_index:
index += 1
continue
if not os.path.exists(outdir):
os.makedirs(outdir)
outname = os.path.join(outdir, str(cam_id)+"_"+v_id+"_"+str(index)+".jpg")
print ("Current frame: ", v_id, str(index))
cv2.imwrite(outname, frame)
height, width, _ = frame.shape
else:
break
index += 1
img_size = (width, height)
return img_size
def instance2xml_base(anno, bbox_type='xyxy'):
"""bbox_type: xyxy (xmin, ymin, xmax, ymax); xywh (xmin, ymin, width, height)"""
assert bbox_type in ['xyxy', 'xywh']
E = objectify.ElementMaker(annotate=False)
anno_tree = E.annotation(
#E.folder('VOC2014_instance/person'),
E.folder('VOC'),
E.filename(anno['id']),
E.source(
E.database('Caltech pedestrian'),
E.annotation('Caltech pedestrian'),
E.image('Caltech pedestrian'),
E.url('None')
),
E.size(
E.width(640),
E.height(480),
E.depth(3)
),
E.segmented(0),
)
for index, bbox in enumerate(anno['bbox']):
bbox = [float(x) for x in bbox]
if bbox_type == 'xyxy':
xmin, ymin, w, h = bbox
xmax = (xmin+w) ##是否越界
ymax = ymin+h
else:
xmin, ymin, xmax, ymax = bbox
E = objectify.ElementMaker(annotate=False)
anno_tree.append(
E.object(
E.name(anno['label']),
E.bndbox(
E.xmin(xmin),
E.ymin(ymin),
E.xmax(xmax),
E.ymax(ymax)
),
E.pose('Unspecified'),
E.difficult(0),
E.occlusion(anno["occlusion"][index])
)
)
return anno_tree
def parse_anno_file(vbb_inputdir, seq_inputdir, vbb_outputdir, seq_outputdir):
# annotation sub-directories in hda annotation input directory
assert os.path.exists(vbb_inputdir)
sub_dirs = os.listdir(vbb_inputdir) #对应set00,set01...
for sub_dir in sub_dirs:
print ("Parsing annotations of camera: ", sub_dir)
cam_id = sub_dir
#获取某一个子set下面的所有vbb文件
vbb_files = glob.glob(os.path.join(vbb_inputdir, sub_dir, "*.vbb"))
for vbb_file in vbb_files:
#返回一个vbb文件中所有的帧的标注结果
annos = vbb_anno2dict(vbb_file, cam_id)
if annos:
#组成xml文件的存储文件夹，形如“/Users/chenguanghao/Desktop/Caltech/xmlresult/”
vbb_outdir = vbb_outputdir
#print("jyye-----------11111")
#如果不存在
if not os.path.exists(vbb_outdir):
os.makedirs(vbb_outdir)
for filename, anno in sorted(annos.items(), key=lambda x: x[0]):
if "bbox" in anno:
anno_tree = instance2xml_base(anno)
outfile = os.path.join(vbb_outdir, os.path.splitext(filename)[0]+".xml")
print ("Generating annotation xml file of picture: ", filename)
#pretty(anno_tree)
#生成最终的xml文件，对应一张图片
etree.ElementTree(anno_tree).write(outfile, pretty_print=True)
def visualize_bbox(xml_file, img_file):
import cv2
tree = etree.parse(xml_file)
# load image
image = cv2.imread(img_file)
origin = cv2.imread(img_file)
# 获取一张图片的所有bbox
for bbox in tree.xpath('//bndbox'):
coord = []
for corner in bbox.getchildren():
coord.append(int(float(corner.text)))
print (coord)
cv2.rectangle(image, (coord[0], coord[1]), (coord[2], coord[3]), (0, 0, 255), 2)
# visualize image
cv2.imshow("test", image)
cv2.imshow('origin',origin)
cv2.waitKey(0)
def main():
vbb_inputdir = "F:\\data\\annotations"
vbb_outputdir = "F:\\data\\xmlresult"
seq_inputdir = "F:\\data\\seq"
seq_outputdir = "F:\\data\\img"
parse_anno_file(vbb_inputdir, seq_inputdir, vbb_outputdir, seq_outputdir)
"""
下面这段是测试代码
"""
"""
xml_file = "/Users/chenguanghao/Desktop/Caltech/xmlresult/set07/bbox/set07_V000_4.xml"
img_file = "/Users/chenguanghao/Desktop/Caltech/JPEG/set07/V000/4.jpg"
visualize_bbox(xml_file, img_file)
"""
if __name__ == "__main__":
main()