I'm trying to convert custom tensorflow model to IR with Model Optimizer.
But, I've got error!
here are my command and error message.
C:\Program Files (x86)\IntelSWTools\openvino_2019.1.133\deployment_tools\model_optimizer>python mo_tf.py --input_model d:\openVINO\frozen_model_tf_1.14.pb --input keep_probabilty,input_image --input_shape (1),(1,40,40,1) --output inference/prediction --output_dir d:\openVINO
Model Optimizer arguments:
- Path to the Input Model: d:\openVINO\frozen_model_tf_1.14.pb
- Path for generated IR: d:\openVINO
- IR output name: frozen_model_tf_1.14
- Log level: ERROR
- Batch: Not specified, inherited from the model
- Input layers: keep_probabilty,input_image
- Output layers: inference/prediction
- Input shapes: (1),(1,40,40,1)
- 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: 2019.1.0-341-gc9b66a2
[ ERROR ] Can't permute attrs for node EltwiseReshapeNormalization. Error message: only integer scalar arrays can be converted to a scalar index
Please, help me!!
Thank you for your quick reply.
Actually, I produced a frozen model on tensorflow 1.9 first
It gave me a same error message.
So, I upgraded tensorflow 1.14 and produced a frozen model on it.
Is any possible other reason?
// my model info
C:\Program Files (x86)\IntelSWTools\openvino_2019.1.133\deployment_tools\model_optimizer\mo\utils>python summarize_graph.py --input_model "d:\openVINO\frozen_model_tf_1.9.pb"
2 input(s) detected:
Name: keep_probabilty, type: float32, shape: <unknown>
Name: input_image, type: float32, shape: (-1,40,40,1)
1 output(s) detected:
Dear park, kyungja,
Can you tell me the kind of Tensorflow model you're having issues with ? Is it an Object Detection API model ? SSD ? Faster RCNN ? If it's a Tensorflow Object Detection API model, then you must follow the below instructions:
Please report back here with your results.
Dear park, kyungja,
Please run downloader.py under C:\Program Files (x86)\IntelSWTools\openvino_2019.1.148\deployment_tools\tools\model_downloader . Do python3 downloader.py --all . After completing that you will see a few semantic segmentation models that we also support, cascaded_unet, deeplab, dilation. Is the model you're trying one of these ?
If it's not, please give me a link to your model (I assume that it's a public model).
I've already tested public semantic segmentation models.
There are no problem.
I want to have application specific model.
I designed my network and learned the model with my own image sets.
I can't give you my model publicly.
But, I can send it to you by email.
Please, let me know your email address.