Darkflow: 训练结果损失：nan 平均损失：nan

大家好，
抱歉，这是我第一次使用任何类型的对象检测，实际上我第一次使用 python。 在尝试训练我的数据集时，我得到的结果是 nan。
我收到的错误是：
运行时警告：在 sqrt 中遇到无效值
obj[4] = np.sqrt(obj[4])

示例注释 xml 文件

<annotation>
  <folder>images</folder>
  <filename>000006.png</filename>
  <segmented>0</segmented>
  <size>
    <width>225</width>
    <height>225</height>
    <depth>3</depth>
  </size>
  <object>
    <name>person</name>
    <pose>Unspecified</pose>
    <truncated>0</truncated>
    <difficult>0</difficult>
    <bndbox>
      <xmin>35</xmin>
      <ymin>93</ymin>
      <xmax>45</xmax>
      <ymax>45</ymax>
    </bndbox>
  </object>
  <object>
    <name>person</name>
    <pose>Unspecified</pose>
    <truncated>0</truncated>
    <difficult>0</difficult>
    <bndbox>
      <xmin>69</xmin>
      <ymin>94</ymin>
      <xmax>77</xmax>
      <ymax>77</ymax>
    </bndbox>
  </object>
  <object>
    <name>person</name>
    <pose>Unspecified</pose>
    <truncated>0</truncated>
    <difficult>0</difficult>
    <bndbox>
      <xmin>129</xmin>
      <ymin>85</ymin>
      <xmax>136</xmax>
      <ymax>136</ymax>
    </bndbox>
  </object>
  <object>
    <name>person</name>
    <pose>Unspecified</pose>
    <truncated>0</truncated>
    <difficult>0</difficult>
    <bndbox>
      <xmin>145</xmin>
      <ymin>98</ymin>
      <xmax>153</xmax>
      <ymax>153</ymax>
    </bndbox>
  </object>
  <object>
    <name>person</name>
    <pose>Unspecified</pose>
    <truncated>0</truncated>
    <difficult>0</difficult>
    <bndbox>
      <xmin>81</xmin>
      <ymin>143</ymin>
      <xmax>92</xmax>
      <ymax>92</ymax>
    </bndbox>
  </object>
  <object>
    <name>person</name>
    <pose>Unspecified</pose>
    <truncated>0</truncated>
    <difficult>0</difficult>
    <bndbox>
      <xmin>185</xmin>
      <ymin>188</ymin>
      <xmax>195</xmax>
      <ymax>195</ymax>
    </bndbox>
  </object>
  <object>
    <name>person</name>
    <pose>Unspecified</pose>
    <truncated>0</truncated>
    <difficult>0</difficult>
    <bndbox>
      <xmin>77</xmin>
      <ymin>189</ymin>
      <xmax>93</xmax>
      <ymax>93</ymax>
    </bndbox>
  </object>
  <object>
    <name>person</name>
    <pose>Unspecified</pose>
    <truncated>0</truncated>
    <difficult>0</difficult>
    <bndbox>
      <xmin>75</xmin>
      <ymin>204</ymin>
      <xmax>89</xmax>
      <ymax>89</ymax>
    </bndbox>
  </object>
</annotation>

配置文件

[net]
batch=64
subdivisions=8
width=416
height=416
channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1

learning_rate=0.001
max_batches = 40100
policy=steps
steps=-1,100,20000,30000
scales=.1,10,.1,.1

[convolutional]
batch_normalize=1
filters=16
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=1

[convolutional]
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky

###########

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=1024
activation=leaky

[convolutional]
size=1
stride=1
pad=1
filters=30
activation=linear

[region]
anchors = 1.08,1.19,  3.42,4.41,  6.63,11.38,  9.42,5.11,  16.62,10.52
bias_match=1
classes=1
coords=4
num=5
softmax=1
jitter=.2
rescore=1

object_scale=5
noobject_scale=1
class_scale=1
coord_scale=1

absolute=1
thresh = .5
random=1

我希望有人能指出我正确的方向。 这是我第一次尝试训练自己的模型。
谢谢，
李