Tensorflow对象检测中止，InvalidArgumentError:索引[0]=2不在[0,1]中

我试图在自己的数据集上训练tensorflow对象检测

我做了什么？

• 使用

  ssd\u mobilenet\u v1\u pets.config

  作为基础，创建我自己的管道配置。调整

  num\u类

  和所有其他路径特定部分，以匹配我的环境

• 从as检查点使用ssd_mobilenet_v1_coco

• 已创建包含所有标签的标签映射文件（第一个索引从1开始）

• 从我的数据集创建了一个

  TFRecord

  文件（脚本基于）

出了什么问题？

开始培训时，请：

python tensorflow\u models/research/object\u detection/train.py--pipeline\u config\u path=/home/playway/ssd\u mobilenet\u v1.config--train\u dir=/tmp/bla/

Traceback (most recent call last):
  File "tensorflow_models/research/object_detection/train.py", line 198, in <module>
    tf.app.run()
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 48, in run
    _sys.exit(main(_sys.argv[:1] + flags_passthrough))
  File "tensorflow_models/research/object_detection/train.py", line 194, in main
    worker_job_name, is_chief, FLAGS.train_dir)
  File "/home/playground/tensorflow_models/research/object_detection/trainer.py", line 296, in train
    saver=saver)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/slim/python/slim/learning.py", line 767, in train
    sv.stop(threads, close_summary_writer=True)
  File "/usr/lib/python2.7/contextlib.py", line 35, in __exit__
    self.gen.throw(type, value, traceback)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/supervisor.py", line 964, in managed_session
    self.stop(close_summary_writer=close_summary_writer)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/supervisor.py", line 792, in stop
    stop_grace_period_secs=self._stop_grace_secs)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/coordinator.py", line 389, in join
    six.reraise(*self._exc_info_to_raise)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/queue_runner_impl.py", line 238, in _run
    enqueue_callable()
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1235, in _single_operation_run
    target_list_as_strings, status, None)
  File "/usr/lib/python2.7/contextlib.py", line 24, in __exit__
    self.gen.next()
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/errors_impl.py", line 466, in raise_exception_on_not_ok_status
    pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: indices[0] = 2 is not in [0, 1)
         [[Node: cond/RandomCropImage/PruneCompleteleyOutsideWindow/Gather/Gather_1 = Gather[Tindices=DT_INT64, Tparams=DT_INT64, validate_indices=true, _device="/job:localhost/replica:0/task:0/cpu:0"](cond/RandomCropImage/PruneCompleteleyOutsideWindow/Gather/Gather_1/Switch:1, cond/RandomCropImage/PruneCompleteleyOutsideWindow/Reshape)]]

edit添加了一些代码，显示如何生成

TFRecord

文件。整个脚本稍微长一点，但我尝试将其缩减为仅显示相关部分。如果遗漏了您感兴趣的内容，请告诉我

CATEGORIES_TO_TRAIN = ["apple", "dog", "cat"]

def createTFExample(img):
    imageFormat = ""
    if img.format == 'JPEG':
        imageFormat = b'jpeg'
    elif img.format == 'PNG':
        imageFormat = b'png'
    else:
        print 'Unknown Image format %s' %(img.format,)
        return None

    width, height = img.size
    filename = str(img.filename)
    encodedImageData = img.bytesIO

    xmins = []
    xmaxs = []
    ymins = []
    ymaxs = []

    for annotation in img.annotations:
        xmins.append((annotation.left / width))
        xmaxs.append((annotation.left + annotation.width) / width)
        ymins.append((annotation.top / height))
        ymaxs.append((annotation.top + annotation.height) / height)

    #we might have some images in our dataset, which don't have a annotation, skip those
    if((len(xmins) == 0) or (len(xmaxs) == 0) or (len(ymins) == 0) or (len(ymaxs) == 0)):
        return None

    label = [img.label.encode('utf8')]
    classes = [(CATEGORIES_TO_TRAIN.index(img.label) + 1)] #class indexes start with 1


    tf_example = tf.train.Example(features=tf.train.Features(feature={
      'image/height': dataset_util.int64_feature(height),
      'image/width': dataset_util.int64_feature(width),
      'image/filename': dataset_util.bytes_feature(filename),
      'image/source_id': dataset_util.bytes_feature(filename),
      'image/encoded': dataset_util.bytes_feature(encodedImageData),
      'image/format': dataset_util.bytes_feature(imageFormat),
      'image/object/bbox/xmin': dataset_util.float_list_feature(xmins),
      'image/object/bbox/xmax': dataset_util.float_list_feature(xmaxs),
      'image/object/bbox/ymin': dataset_util.float_list_feature(ymins),
      'image/object/bbox/ymax': dataset_util.float_list_feature(ymaxs),
      'image/object/class/text': dataset_util.bytes_list_feature(label),
      'image/object/class/label': dataset_util.int64_list_feature(classes),
    }))
    return tf_example


def createTfRecordFile(images):
    writer = tf.python_io.TFRecordWriter(TFRECORD_OUTPUT_PATH)
    for img in images:
        t = createTFExample(img)
        if t is not None:
            writer.write(t.SerializeToString())

    writer.close()

---

非常感谢为我指明正确方向的任何帮助！

我也遇到了类似的问题，但是让

标签

列表和

类

列表与边界框元素具有相同的长度为我解决了这个问题

具体而言，在

createTFExample（）

中，

label=[img.label.encode（'utf8'）]

和

classes=[（CATEGORIES\u TO\u TRAIN.index（img.label）+1）]

中的元素应与边界框注释列表的元素相对应：

xmins = []
xmaxs = []
ymins = []
ymaxs = []

for annotation in img.annotations:
    xmins.append((annotation.left / width))
    xmaxs.append((annotation.left + annotation.width) / width)
    ymins.append((annotation.top / height))
    ymaxs.append((annotation.top + annotation.height) / height)

根据您的代码结构，我假设每个

img

对象有一个对象类型，但在这种情况下，编写

label = [img.label.encode('utf8')] * len(xmins)  
classes = [(CATEGORIES_TO_TRAIN.index(img.label) + 1)] * len(xmins)

或者使用图像中提供对象数量的任何元素，以便标签和类以及边界框列表具有相同的长度。
如果一个

img

对象中存在多种类型的对象，则创建一个对象名称和类别ID列表，其中内部元素的索引与注释列表的索引匹配

结果列表应如下所示：

xmins = [a_xmin, b_xmin, c_xmin]
ymins = [a_ymin, b_ymin, c_ymin]
xmaxs = [a_xmax, b_xmax, c_xmax]
ymaxs = [a_ymax, b_ymax, c_ymax]
labels = [a_label, b_label, c_label]
classes = [a_classid, b_classid, c_classid]

---

这解决了我的问题，希望这能有所帮助！

我可能完全错了，但我认为pets.config中建议的设置与您使用的coco模型是分开的，因此它会对形状产生抱怨。请尝试改用coco模型设置。让我知道它是否有效谢谢@eshirima的建议-非常感谢！我刚刚试过，但不幸的是，它现在失败了，错误消息略有不同（我用回溯更新了原始帖子）在标签映射中，是否还有索引为0的类作为背景/无对象？@gdelab感谢您的帮助！我的标签映射看起来类似于，但不是37个项目，而是只有3个项目。我的标签映射也从1开始，因此那里没有索引为0的类。我需要一个吗？我想是的，但显然我错了。对不起，回复太晚了。你完全正确，这完全解决了我的问题。非常感谢你的帮助，非常感谢！

xmins = [a_xmin, b_xmin, c_xmin]
ymins = [a_ymin, b_ymin, c_ymin]
xmaxs = [a_xmax, b_xmax, c_xmax]
ymaxs = [a_ymax, b_ymax, c_ymax]
labels = [a_label, b_label, c_label]
classes = [a_classid, b_classid, c_classid]