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I used the code below to convert my model. But it does not work.
sudo python3 mo_tf.py --input_model /home/ls201/Desktop/veh_class_faster_rcnn/frozen_inference_graph.pb --transformations_config /opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/faster_rcnn_support_api_v1.14.json --tensorflow_object_detection_api_pipeline_config /home/ls201/Desktop/veh_class_faster_rcnn/pipeline.config
the output is:
Model Optimizer arguments:
Common parameters:
- Path to the Input Model: /home/ls201/Desktop/veh_class_faster_rcnn/frozen_inference_graph.pb
- Path for generated IR: /opt/intel/openvino_2020.1.023/deployment_tools/model_optimizer/.
- IR output name: frozen_inference_graph
- 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: /home/ls201/Desktop/veh_class_faster_rcnn/pipeline.config
- Operations to offload: None
- Patterns to offload: None
- Use the config file: None
Model Optimizer version: 2020.1.0-61-gd349c3ba4a
Illegal instruction
link for model and pipeline config
https://drive.google.com/open?id=1vpVoYAfA5IdOcXNLgyelEUkENRHLRW_P
Link Copied
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Hi Maverick,
It looks like the pipeline.config file is empty, could you double check?
Also, please share additional information about the model.
- Is it a pre-trained model or custom trained model?
- If it's custom trained model, what base model was used for training?
- Which version of TensorFlow was used for training?
- How did you freeze the model?
Regards,
Jesus
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I have the same problem but when I'm installing the robot_devkit, it says "Illegal instruction", this is the output:
Model Optimizer arguments:
Common parameters:
- Path to the Input Model: /home/ramon/Downloads/models/mask_rcnn_inception_v2_coco_2018_01_28/frozen_inference_graph.pb
- Path for generated IR: /opt/openvino_toolkit/models/segmentation/output/FP32
- IR output name: frozen_inference_graph
- 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: 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: /home/ramon/Downloads/models/mask_rcnn_inception_v2_coco_2018_01_28/pipeline.config
- Use the config file: /opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/mask_rcnn_support.json
Model Optimizer version:
/home/ramon/robot_devkit/packages/perception/deps/33-openvino.deps: line 14: 18813 Illegal instruction sudo python3 /opt/intel/openvino/deployment_tools/model_optimizer/mo_tf.py --input_model frozen_inference_graph.pb --tensorflow_use_custom_operations_config /opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/mask_rcnn_support.json --tensorflow_object_detection_api_pipeline_config pipeline.config --reverse_input_channels --output_dir /opt/openvino_toolkit/models/segmentation/output/FP32
Because of this it can't finish the process of installation of robot_devkit, specifically the problem comes out when I run the command: ./demo/rdk_install.sh , I'm following the instructions of this link: https://intel.github.io/robot_devkit_doc/pages/install.html
I've already have the two cameras and the neural compute stick 2,
the file content of the file: mask_rcnn_inception_v2_coco_2018_01_28/pipeline.config
is:
model {
faster_rcnn {
number_of_stages: 3
num_classes: 90
image_resizer {
keep_aspect_ratio_resizer {
min_dimension: 800
max_dimension: 1365
}
}
feature_extractor {
type: "faster_rcnn_inception_v2"
first_stage_features_stride: 16
}
first_stage_anchor_generator {
grid_anchor_generator {
height_stride: 16
width_stride: 16
scales: 0.25
scales: 0.5
scales: 1.0
scales: 2.0
aspect_ratios: 0.5
aspect_ratios: 1.0
aspect_ratios: 2.0
}
}
first_stage_box_predictor_conv_hyperparams {
op: CONV
regularizer {
l2_regularizer {
weight: 0.0
}
}
initializer {
truncated_normal_initializer {
stddev: 0.00999999977648
}
}
}
first_stage_nms_score_threshold: 0.0
first_stage_nms_iou_threshold: 0.699999988079
first_stage_max_proposals: 100
first_stage_localization_loss_weight: 2.0
first_stage_objectness_loss_weight: 1.0
initial_crop_size: 14
maxpool_kernel_size: 2
maxpool_stride: 2
second_stage_box_predictor {
mask_rcnn_box_predictor {
fc_hyperparams {
op: FC
regularizer {
l2_regularizer {
weight: 0.0
}
}
initializer {
variance_scaling_initializer {
factor: 1.0
uniform: true
mode: FAN_AVG
}
}
}
use_dropout: false
dropout_keep_probability: 1.0
conv_hyperparams {
op: CONV
regularizer {
l2_regularizer {
weight: 0.0
}
}
initializer {
truncated_normal_initializer {
stddev: 0.00999999977648
}
}
}
predict_instance_masks: true
mask_prediction_conv_depth: 0
mask_height: 15
mask_width: 15
mask_prediction_num_conv_layers: 2
}
}
second_stage_post_processing {
batch_non_max_suppression {
score_threshold: 0.300000011921
iou_threshold: 0.600000023842
max_detections_per_class: 100
max_total_detections: 100
}
score_converter: SOFTMAX
}
second_stage_localization_loss_weight: 2.0
second_stage_classification_loss_weight: 1.0
second_stage_mask_prediction_loss_weight: 4.0
}
}
train_config {
batch_size: 1
data_augmentation_options {
random_horizontal_flip {
}
}
optimizer {
momentum_optimizer {
learning_rate {
manual_step_learning_rate {
initial_learning_rate: 0.000199999994948
schedule {
step: 0
learning_rate: 0.000199999994948
}
schedule {
step: 900000
learning_rate: 1.99999994948e-05
}
schedule {
step: 1200000
learning_rate: 1.99999999495e-06
}
}
}
momentum_optimizer_value: 0.899999976158
}
use_moving_average: false
}
gradient_clipping_by_norm: 10.0
fine_tune_checkpoint: "PATH_TO_BE_CONFIGURED/model.ckpt"
from_detection_checkpoint: true
num_steps: 200000
}
train_input_reader {
label_map_path: "PATH_TO_BE_CONFIGURED/mscoco_label_map.pbtxt"
tf_record_input_reader {
input_path: "PATH_TO_BE_CONFIGURED/mscoco_train.record"
}
}
eval_config {
num_examples: 8000
max_evals: 10
use_moving_averages: false
}
eval_input_reader {
label_map_path: "PATH_TO_BE_CONFIGURED/mscoco_label_map.pbtxt"
shuffle: false
num_readers: 1
tf_record_input_reader {
input_path: "PATH_TO_BE_CONFIGURED/mscoco_val.record"
}
}
the only advertisement that I see is "ILLEGAL INSTRUCTION" but I haven't found any log file to see details.
I Hope someone can help,
Thanks regards .
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