Question

我正在尝试将MNIST图像用于许多分类器，但是由于某种原因，它现在会产生此错误。（之前是正确的，但我更改了InceptionV3的来源）。这是提供的错误：


InvalidArgumentError                      Traceback (most recent call last)
~\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\framework\ops.py in _create_c_op(graph, node_def, inputs, control_inputs)
   1627  try:
-> 1628     c_op = c_api.TF_FinishOperation(op_desc)
   1629   except errors.InvalidArgumentError as e:

InvalidArgumentError: Negative dimension size caused by subtracting 3 from 1 for 'InceptionV3/InceptionV3/Mixed_6a/Branch_0/Conv2d_1a_1x1/Conv2D' (op: 'Conv2D') with input shapes: [?,1,1,288], [3,3,288,384].

在处理上述异常期间，发生了另一个异常：

ValueError                                Traceback (most recent call last)
<ipython-input-6-db92b294fe8d> in <module>
----> 1 fileImg1.play("Saliency")

~\OneDrive\Documenti\GitHub\cexplainer\src\Xlib.py in play(self, ex)
    193         if (ex not in self.dictImgModel):
    194             explainer = self.dictImgExplainer[ex]
--> 195             img = prepareImage(self.name,self.PATH,self.SHAPE_1,self.SHAPE_2,self.dataset,self.X_vec,self.y_vec,explainer,label)
    196             self.dictImgModel[ex] = img
    197 

~\OneDrive\Documenti\GitHub\cexplainer\src\algorithms\KDD.py in prepareImage(name, PATH, SHAPE_1, SHAPE_2, dataset, X_vec, y_vec, explainer, label)
    438                 with slim.arg_scope(inception.inception_v3_arg_scope()):
    439                     _, end_points = inception.inception_v3(processed_images, is_training=False,
--> 440                                                               num_classes=10)
    441                     # Restore the checkpoint
    442                     sess = tf.Session(graph=graph)

~\AppData\Roaming\Python\Python36\site-packages\tensorflow\contrib\slim\python\slim\nets\inception_v3.py in inception_v3(inputs, num_classes, is_training, dropout_keep_prob, min_depth, depth_multiplier, prediction_fn, spatial_squeeze, reuse, scope)
    578           scope=scope,
    579           min_depth=min_depth,
--> 580           depth_multiplier=depth_multiplier)
    581 
    582       # Auxiliary Head logits

一些建议？

Answer 1

MNIST是1个通道图像的集合。所有经过预训练的模型都使用3通道（rgb）图像。您可以重复3次单通道图像来绕过此冲突。

使用InceptionV3的MNIST的错误输入形状

1 个答案: