tensorflow openvino ssd-mobilnet coco自定义数据集错误输入层

问题描述

因此，我正在使用TensorFlow SSD-Mobilnet V1可可数据集.我已经对自己的数据集进行了进一步的培训，但是当我尝试将其转换为OpenVino IR以便在具有Movidius Chip的Raspberry PI上运行它时.我收到错误消息

So, I'm using TensorFlow SSD-Mobilnet V1 coco dataset. That I have further trained on my own dataset but when I try to convert it to OpenVino IR to run it on Raspberry PI with Movidius Chip. I get an error

➜  utils sudo python3 summarize_graph.py --input_model ssd.pb 
WARNING: Logging before flag parsing goes to stderr.
W0722 17:17:05.565755 4678620608 __init__.py:308] Limited tf.compat.v2.summary API due to missing TensorBoard installation.
W0722 17:17:06.696880 4678620608 deprecation_wrapper.py:119] From ../../mo/front/tf/loader.py:35: The name tf.GraphDef is deprecated. Please use tf.compat.v1.GraphDef instead.

W0722 17:17:06.697348 4678620608 deprecation_wrapper.py:119] From ../../mo/front/tf/loader.py:109: The name tf.MetaGraphDef is deprecated. Please use tf.compat.v1.MetaGraphDef instead.

W0722 17:17:06.697680 4678620608 deprecation_wrapper.py:119] From ../../mo/front/tf/loader.py:235: The name tf.NodeDef is deprecated. Please use tf.compat.v1.NodeDef instead.

1 input(s) detected:
Name: image_tensor, type: uint8, shape: (-1,-1,-1,3)
7 output(s) detected:
detection_boxes
detection_scores
detection_multiclass_scores
detection_classes
num_detections
raw_detection_boxes
raw_detection_scores

当我尝试将ssd.pb(冻结模型)转换为OpenVino IR时

When I try to convert the ssd.pb(frozen model) to OpenVino IR

➜  model_optimizer sudo python3 mo_tf.py --input_model ssd.pb          
Password:
Model Optimizer arguments:
Common parameters:
    - Path to the Input Model:  /opt/intel/openvino_2019.1.144/deployment_tools/model_optimizer/ssd.pb
    - Path for generated IR:    /opt/intel/openvino_2019.1.144/deployment_tools/model_optimizer/.
    - IR output name:   ssd
    - Log level:    ERROR
    - Batch:    Not specified, inherited from the model
    - Input layers:     Not specified, inherited from the model
    - Output layers:    Not specified, inherited from the model
    - Input shapes:     Not specified, inherited from the model
    - Mean values:  Not specified
    - Scale values:     Not specified
    - Scale factor:     Not specified
    - Precision of IR:  FP32
    - Enable fusing:    True
    - Enable grouped convolutions fusing:   True
    - Move mean values to preprocess section:   False
    - Reverse input channels:   False
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:  None
    - Operations to offload:    None
    - Patterns to offload:  None
    - Use the config file:  None
Model Optimizer version:    2019.1.1-83-g28dfbfd
WARNING: Logging before flag parsing goes to stderr.
E0722 17:24:22.964164 4474824128 infer.py:158] Shape [-1 -1 -1  3] is not fully defined for output 0 of "image_tensor". Use --input_shape with positive integers to override model input shapes.
E0722 17:24:22.964462 4474824128 infer.py:178] Cannot infer shapes or values for node "image_tensor".
E0722 17:24:22.964554 4474824128 infer.py:179] Not all output shapes were inferred or fully defined for node "image_tensor". 
 For more information please refer to Model Optimizer FAQ (<INSTALL_DIR>/deployment_tools/documentation/docs/MO_FAQ.html), question #40. 
E0722 17:24:22.964632 4474824128 infer.py:180] 
E0722 17:24:22.964720 4474824128 infer.py:181] It can happen due to bug in custom shape infer function <function tf_placeholder_ext.<locals>.<lambda> at 0x12ab64bf8>.
E0722 17:24:22.964787 4474824128 infer.py:182] Or because the node inputs have incorrect values/shapes.
E0722 17:24:22.964850 4474824128 infer.py:183] Or because input shapes are incorrect (embedded to the model or passed via --input_shape).
E0722 17:24:22.965915 4474824128 infer.py:192] Run Model Optimizer with --log_level=DEBUG for more information.
E0722 17:24:22.966033 4474824128 main.py:317] Exception occurred during running replacer "REPLACEMENT_ID" (<class 'extensions.middle.PartialInfer.PartialInfer'>): Stopped shape/value propagation at "image_tensor" node. 
 For more information please refer to Model Optimizer FAQ (<INSTALL_DIR>/deployment_tools/documentation/docs/MO_FAQ.html), question #38.

您认为我们应该如何解决此问题?

How do you think we should fix this?

推荐答案

我将OpenVINO更新为OpenVINO工具包R2 2019&使用以下命令，我能够生成IR文件

I updated my OpenVINO to OpenVINO toolkit R2 2019 & using the below command I was able to generate IR file

python3 ~/intel/openvino/deployment_tools/model_optimizer/mo_tf.py --input_model frozen_inference_graph.pb --tensorflow_use_custom_operations_config ~/intel/openvino/deployment_tools/model_optimizer/extension/front/tf/ssd_support_api_v1.14.json --tensorflow_object_detection_api_pipeline_config pipeline.config -b 1 --data_type FP16 --reverse_input_channels

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