为Tensorflow对象检测API创建PASCAL Voc [英] Create PASCAL Voc for Tensorflow Object Detection API
问题描述
这个问题是这个问题的扩展.
TLDR; 我正在尝试使用自己的数据集训练TS对象检测API.为了进行概念验证，我决定将数据集遵循Pascal VOC 2012基准测试.
TLDR; I'm trying to train the TS Object Detection API using my own dataset. For proof of concept, I decided to adhere my dataset to the Pascal VOC 2012 benchmark.
此刻，我正在尝试从我的Pascal VOC注释创建TFRecord.
At the moment, I am trying to create a TFRecord from my Pascal VOC annotations.
在这行中， em> create_pascal_tf_record.py 脚本，他们只是在抓住飞机的 descriptor ；缺少更好的单词，文本文件.为什么会这样呢?其他类的描述符又如何呢?
Looking at this line in their create_pascal_tf_record.py script, they're just grabbing the aeroplane's descriptor; lack of a better word, text file. Why is this so? What about the other classes' descriptors?
旁注
此文件；与
This file; titled aeroplane_train.txt, was included along with the Pascal VOC 2012 dataset inside VOC2012/ImageSets/Main/.
窥视文件显示第一列代表图像名称，-1或1表示特定图像是否包含我们感兴趣的类(飞机).
A peek into the file shows that the first column represents an image name and the -1 or 1 states whether that particular image consists of the class(aeroplane) we're interested in.
aeroplane_train.txt 文件的部分内容:
Partial contents of the aeroplane_train.txt file:
2008_000008 -1
2008_000015 -1
2008_000019 -1
2008_000023 -1
2008_000028 -1
2008_000033 1
2008_000036 -1
2008_000037 1
2008_000041 -1
2008_000045 -1
2008_000053 -1
2008_000060 -1
2008_000066 -1
2008_000070 -1
2008_000074 -1
2008_000085 -1
2008_000089 -1
2008_000093 -1
2008_000095 -1
2008_000096 -1
2008_000097 -1
2008_000099 -1
2008_000103 -1
2008_000105 -1
2008_000109 -1
2008_000112 -1
2008_000128 -1
2008_000131 -1
2008_000132 -1
2008_000141 -1
推荐答案
我在此处.最重要的是，我们目前仅查看aeroplane_train.txt文件的第一列(与其他xxx_train.txt文件相同)，并让我们找出训练集中每个图像的路径.
I answered a similar question here. The punchline is that we currently only look at the first column of the aeroplane_train.txt file (which is the same as the other xxx_train.txt files) and lets us figure out the path for each image in the training set.
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