我需要一个工具来用矩形边界框标注图像。输出将采用Pascal VOC XML格式。标注和图像将作为训练数据集的一部分，用于卷积神经网络进行对象检测。我将手动标注图像。
我考虑过以下工具，但它们不支持Pascal VOC格式。
有没有可以节省我时间的标注工具？
回答：
这个Python代码片段将Sloth JSON转换为Pascal VOC XML格式。
def make_anno(): zind = 0 for z in data: print zind filename = data[zind]["filename"] print filename head, tail = os.path.split(filename) basename, file_extension = os.path.splitext(tail) f = open(basename + '.xml','w') line = "<annotation>" + '\n' f.write(line) line = '\t\t<folder>' + "folder" + '</folder>' + '\n' f.write(line) line = '\t\t<filename>' + tail + '</filename>' + '\n' f.write(line) line = '\t\t<source>\n\t\t<database>Source</database>\n\t</source>\n' f.write(line) im=Image.open('/home/location/VOCdevkit/newdataset/img/' + tail) (width, height) = im.size line = '\t<size>\n\t\t<width>'+ str(width) + '</width>\n\t\t<height>' + str(height) + '</height>\n\t' line += '\t<depth>Unspecified</depth>\n\t</size>' f.write(line) line = '\n\t<segmented>Unspecified</segmented>' f.write(line) ind = 0 for i in data[zind]["annotations"]: line = '\n\t<object>' line += '\n\t\t<name>Name</name>\n\t\t<pose>Unspecified</pose>' line += '\n\t\t<truncated>Unspecified</truncated>\n\t\t<difficult>Unspecified</difficult>' xmin = (data[zind]["annotations"][ind]["x"]) line += '\n\t\t<bndbox>\n\t\t\t<xmin>' + str(xmin) + '</xmin>' ymin = (data[zind]["annotations"][ind]["y"]) line += '\n\t\t\t<ymin>' + str(ymin) + '</ymin>' width = (data[zind]["annotations"][ind]["width"]) height = (data[zind]["annotations"][ind]["height"]) xmax = xmin + width ymax = ymin + height line += '\n\t\t\t<xmax>' + str(xmax) + '</xmax>' line += '\n\t\t\t<ymax>' + str(ymax) + '</ymax>' line += '\n\t\t</bndbox>' line += '\n\t</object>' f.write(line) ind +=1 f.close() zind +=1