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DL workbench accuracy tool is failing by giving status as Accuracy Tool Failed for my faster rcnn inception v2 coco tensorflow object detection model v 1.15. Please help with the Configuration.
I have attached the screenshot of the DL workbench.
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Greetings,
You may try to follow these steps (there's also step by step video here): https://docs.openvinotoolkit.org/latest/workbench_docs_Workbench_DG_Int_8_Quantization.html
Sincerely,
iffa
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Hi,
Thank you for the response.
when i'm trying to optimize model to INT8 using DL workbench, it's giving error as 'resize to input size possible, only for one input layer case'. i have attached screenshot also . Please help out in this issue.
Thanks
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@raushan Calibration of Faster-RCNN with Default method works in DL Workbench 2021.3. AccuracyAware method still requires you to provide a valid Advanced accuracy config.
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Could you help to attach your faster rcnn graph and also your dataset,
So that I could replicate this?.
Sincerely,
Iffa
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Greetings,
Thank you for your question. If you need any additional information from Intel, please submit a new question as Intel is no longer monitoring this thread.
Sincerely,
Iffa
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Hi @raushan ,
Starting from 2021.3 (released at the end of Q1 in 2021) DL Workbench has two modes of accuracy measurement: basic and advanced. https://docs.openvinotoolkit.org/latest/workbench_docs_Workbench_DG_Measure_Accuracy.html
- Basic mode provides simplified and reduced scope of accuracy settings and works for reduced range of models, for example basic mode supports models with only one input. At the same time
- Advanced mode allows to provide a valid accuracy config for the Accuracy Checker tool that is used inside. Therefore, the list of models that you can measure accuracy for is much larger and, for examples, allows to measure accuracy for models with several inputs.
In your particular case, in order to measure accuracy of Faster-RCNN model, you need to use Advanced mode and specify the input metadata layer in the configuration. Here is the example of configuration file that is valid for the following Faster-RCNN model (model with a name faster_rcnn_inception_v2_coco from https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/tf1_detection_zoo.md):
name: faster_rcnn_inception_v2_coco
launchers:
- adapter:
type: ssd
batch: 1
device: CPU
framework: dlsdk
inputs:
- name: image_info
type: CONST_INPUT
value:
- - 600
- 1024
- 1
model: $MODEL_PATH/faster_rcnn_inception_v2_coco.xml
weights: $MODEL_PATH/faster_rcnn_inception_v2_coco.bin
datasets:
- annotation_conversion:
annotation_file: $DATASET_PATH/annotations/instances_val2017_200pictures.json
converter: mscoco_detection
has_background: true
images_dir: $DATASET_PATH/images
use_full_label_map: true
data_source: $DATASET_PATH/images
metrics:
- max_detections: 100
presenter: print_vector
type: coco_precision
name: dataset
postprocessing:
- dst_height: 600
dst_width: 1024
type: faster_rcnn_postprocessing_resize
preprocessing:
- aspect_ratio_scale: fit_to_window
dst_height: 600
dst_width: 1024
type: resize
- dst_height: 600
dst_width: 1024
pad_type: right_bottom
type: padding
subsample_size: 100%
Please note that you might want to specify additional parameters, refer to the Accuracy Checker documentation: https://github.com/openvinotoolkit/open_model_zoo/tree/master/tools/accuracy_checker
If you have any additional questions or proposals, please ask them via the official DL Workbench Discussion Forum: https://github.com/openvinotoolkit/workbench_feedback/discussions.
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