Python 使用opencv dnn readNetFromModelOptimizer时出现错误（应为：'；inputShapeLimitation.size（）==blobShape.size（）'；）

我正在尝试使用转移学习来训练一个用于目标检测的模型，以便与Intel Neural Compute Stick 2（NCS2）一起使用

迄今为止的步骤

使用谷歌COLAB上的tensorflow 1.15，在我的自定义数据集上使用转移学习训练更快\u rcnn\u inception\u v2\u coco\u 2018\u 01\u 28模型

已验证保存的tensorflow模型可与opencv python一起使用tensorflow.saved_model.load进行对象检测

冻结模型并使用如下所示的openvino模型优化器命令创建IR.bin和.xml，以便与opencv python dnn函数一起使用

输出如下

Model Optimizer arguments:
Common parameters:
- Path to the Input Model:  frozen_inference_graph.pb
- Path for generated IR:    /.
- IR output name:   frozen_inference_graph
- Log level:    ERROR
- Batch:    Not specified, inherited from the model
- Input layers:     image_tensor
- Output layers:    detection_scores,detection_boxes,num_detections
- Input shapes:     [1,600,600,3]
- Mean values:  Not specified
- Scale values:     Not specified
- Scale factor:     Not specified
- Precision of IR:  FP16
- Enable fusing:    True
- Enable grouped convolutions fusing:   True
- Move mean values to preprocess section:   False
- Reverse input channels:   True

TensorFlow specific parameters:
- Input model in text protobuf format:  False
- Path to model dump for TensorBoard:   None
- List of shared libraries with TensorFlow custom layers implementation:    None
- Update the configuration file with input/output node names:   None
- Use configuration file used to generate the model with Object Detection API:  pipeline.config
- Use the config file:  None

Model Optimizer version:    
[ WARNING ] Model Optimizer removes pre-processing block of the model which resizes image
keeping aspect ratio. The Inference Engine does not support dynamic image size so the
Intermediate Representation file is generated with the input image size of a fixed size.
The Preprocessor block has been removed. Only nodes performing mean value subtraction and
scaling (if applicable) are kept.
The graph output nodes "num_detections", "detection_boxes", "detection_classes",
"detection_scores" have been replaced with a single layer of type "Detection Output".
Refer to IR catalogue in the documentation for information about this layer.

[ WARNING ]  Network has 2 inputs overall, but only 1 of them are suitable for input
channels reversing.
Suitable for input channel reversing inputs are 4-dimensional with 3 channels
All inputs: {'image_tensor': [1, 3, 600, 600], 'image_info': [1, 3]}
Suitable inputs {'image_tensor': [1, 3, 600, 600]}

[ SUCCESS ] Generated IR version 10 model.
[ SUCCESS ] XML file: /./frozen_inference_graph.xml
[ SUCCESS ] BIN file: /./frozen_inference_graph.bin
[ SUCCESS ] Total execution time: 26.84 seconds. 
[ SUCCESS ] Memory consumed: 617 MB. 

使用opencv python dnn加载转换后的模型 使用openvino ubuntu_dev docker映像openvino/ubuntu18_dev:latest 我运行一个包含以下内容的python脚本

报告以下错误

Traceback (most recent call last):
  File "xxxxxxxxxxxxxx-dnn.py", line 49, in <module>
  
net.setInput(blob)
cv2.error: OpenCV(4.4.0-openvino) ../opencv/modules/dnn/src/dnn.cpp:4017: error:
    (-2:Unspecified error) in function 'void   cv::dnn::dnn4_v20200609::Net::setInput(cv::InputArray, const String&, double, const Scalar&)'
    (expected: 'inputShapeLimitation.size() == blobShape.size()'), where 'inputShapeLimitation.size()' is 2 must be equal to 'blobShape.size()' is 4

回溯（最近一次呼叫最后一次）：
文件“xxxxxxxxx-dnn.py”，第49行，在
net.setInput（blob）
cv2.error:OpenCV（4.4.0-openvino）…/OpenCV/modules/dnn/src/dnn.cpp:4017:error:
函数“void cv:：dnn:：dnn4_v20200609:：Net:：setInput（cv:：InputArray，常量字符串&，双精度，常量标量&）”中的（-2:未指定错误）
（应为：'inputShapeLimitation.size（）==blobShape.size（）'），其中'inputShapeLimitation.size（）'为2必须等于'blobShape.size（）'为4

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有谁能解释一下如何解决这个错误吗？

我建议您尝试将您的模型加载到Openvino的示例中，如下所示：

似乎使用了与blob大小相关的不兼容的大小。您的python脚本可能与动态成形无关

这可能对您有用：

net = cv2.dnn.readNetFromModelOptimizer('frozen_inference_graph.xml',
        'frozen_inference_graph.bin') 
blob = cv2.dnn.blobFromImage(image_from_file)
net.setInput(blob)

Traceback (most recent call last):
  File "xxxxxxxxxxxxxx-dnn.py", line 49, in <module>
  
net.setInput(blob)
cv2.error: OpenCV(4.4.0-openvino) ../opencv/modules/dnn/src/dnn.cpp:4017: error:
    (-2:Unspecified error) in function 'void   cv::dnn::dnn4_v20200609::Net::setInput(cv::InputArray, const String&, double, const Scalar&)'
    (expected: 'inputShapeLimitation.size() == blobShape.size()'), where 'inputShapeLimitation.size()' is 2 must be equal to 'blobShape.size()' is 4