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Draft PR to update the samples

@sfatimar sfatimar requested a review from MaajidKhan April 19, 2022 15:05
## Prerequisites
1. [The Intel<sup>®</sup> Distribution of OpenVINO toolkit](https://docs.openvinotoolkit.org/latest/index.html)
1. [The Intel<sup>®</sup> Distribution of OpenVINO toolkit](https://docs.openvino.ai/latest/openvino_docs_install_guides_install_runtime.html)
Please select Install OpenVINO Runtime using an installer

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Resolved

## Running the ONNXRuntime OpenVINO Execution Provider sample
```bash
python3 tiny_yolov2_obj_detection_sample.py
python3 tiny_yolov2_obj_detection_sample.py --video bottle-detection.mp4 --model tinyyolov2.onnx

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Can we also make passing device type options configurable with the sample.
Default, it should pick OpenVINO-EP CPU.
But the user should also have options to run on other device_types in OpenVINO-EP and also MLAS (default CPU-EP)

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Resolved



## Running the ONNXRuntime OpenVINO Execution Provider sample
```bash

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Also we need to add --h option to this sample

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Resolved

@MaajidKhan
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Is this comment addressed "There is a new error related to API version mismatch with numpy. (see screenshots)"

@MaajidKhan
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Is there a way, the user will be notified that his sample is falling back to MLAS even though he tried to run it on OpenVINO-EP.
If it is falling back to MLAS, the output window also should correctly show that the device_type is MLAS and not OpenVINO-EP device which user tried to ran at the first place.

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Licenses need to be updated for both the samples.
Update in Line 2 in both .py files (yolov4.py, tiny_yolov2_obj_det.py)

change from: Copyright (C) 2021, Intel Corporation
To: Copyright (C) 2021-2022, Intel Corporation

@sfatimar
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Is there a way, the user will be notified that his sample is falling back to MLAS even though he tried to run it on OpenVINO-EP. If it is falling back to MLAS, the output window also should correctly show that the device_type is MLAS and not OpenVINO-EP device which user tried to ran at the first place.

We will have to put some change in code to know if we are doing subgraph partitioning, it is currently not there

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3 participants