ValueError: attempt to get argmax of an empty sequence

墨蓝 2023-06-21 10:23 6阅读 0赞

本文针对faster rcnn训练中出现上述问题及解决的方法进行简单记录。

*  报错信息

2019-12-12 04:51:57.002253: W tensorflow/core/framework/op_kernel.cc:1610] Invalid argument: ValueError: attempt to get argmax of an empty sequence
    Traceback (most recent call last):
    
      File "/usr/local/lib/python3.5/dist-packages/tensorflow_core/python/ops/script_ops.py", line 221, in __call__
        ret = func(*args)
    
      File "/workspace/tf-faster-rcnn-master/tools/../lib/layer_utils/anchor_target_layer.py", line 51, in anchor_target_layer
        argmax_overlaps = overlaps.argmax(axis=1)

*  排查方法

1. 增加文件名信息至训练数据(lib/roi_data_layer/minibatch.py程序的get_minibatch函数)
    blobs['addimages']=roidb[0]['image']   #增加语句 
    blobs['gt_boxes'] = gt_boxes
    
    2. 输出当前训练batch数据的信息(lib/model/train_val.py程序的construct_graph函数)
    blobs = self.data_layer.forward()
    print ('iter{}, info:{}'.format(iter,blobs)) #增加语句
    
    3. 输出当前val batch数据的信息(lib/model/train_val.py程序的construct_graph函数)
    blobs_val = self.data_layer_val.forward()
    print ('iter{}, info_val:{}'.format(iter,blobs)) #增加语句

*  重新运行获得错误数据的图片信息

iter4559, info_val:{'addimages': 'data/JPEGImages/000202.jpg', 'data': array([[[[ -91.9801    ,  -99.9465    , -107.7717    ],
             [ -91.5426    ,  -99.509     , -107.3342    ],
             ...,
    
             [  -6.9801    ,   25.0535    ,    1.2283    ]]]], dtype=float32), 'gt_boxes': array([], shape=(0, 5), dtype=float32), 'im_info': array([600. , 800. ,   1.6], dtype=float32)}

*  解决方法

1.  查看xml标注文件，删除空元素
2.  对于修改文件处理程序的，如pascal\_voc.py，需要确保数据读取中无异常\\

ps：可通过[anchor\_target\_layer.py][anchor_target_layer.py]函数快速输出gt\_boxes的信息

print ('gt_boxes: {}, ahcnors: {}'.format(gt_boxes, anchors))  #添加语句
      overlaps = bbox_overlaps(
        np.ascontiguousarray(anchors, dtype=np.float),
        np.ascontiguousarray(gt_boxes, dtype=np.float))
      argmax_overlaps = overlaps.argmax(axis=1)

Q2: IndexError: list index out of range

加载数据时越界了，有两种情况导致该原因：

1. .pkl文件没有更新，删除后重新生成即可；

2. 旧的中间模型没有删除，导致加载了原有训练模型的参数，引起数据异常；

参考文献：

1.  [tf-faster-rcnn][]

[anchor_target_layer.py]: https://github.com/endernewton/tf-faster-rcnn/blob/master/lib/layer_utils/anchor_target_layer.py
[tf-faster-rcnn]: https://github.com/endernewton/tf-faster-rcnn