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220-yolov5-accuracy-check-and-quantization demo (openvinotoolkit#592)
* Update new demo 306-pytorch-object-detection-accuracy-check-and-quantization * Fix sh command issue for demo 306 * Fix demo 306 code check * Update readme for 306 demo * Update demo 219 * update readme * fix docker build issue * rebase to master * update * update * Update Yolov5 project to 220-demo * Update notebooks/README.md Co-authored-by: Adrian Boguszewski <adekboguszewski@gmail.com> * Update README.md Co-authored-by: Adrian Boguszewski <adekboguszewski@gmail.com> * Update notebooks/220-yolov5-accuracy-check-and-quantization/220-yolov5-accuracy-check-and-quantization.ipynb Co-authored-by: Adrian Boguszewski <adekboguszewski@gmail.com> * update * Update replace os.path to Path func * update * Update to fix onnx issue in Win10 * Update to fix * include in the markdown cell that this process should take a few minutes * Update onnx>=1.11.0 * Update pipfile * Update pipfile * to merge with master commit * Fix pipfile.lock * Fix onnx>=1.11.0,<1.12.0 due py3.6 not support onnx 1.12.0 * Fix onnx>=1.11.0,<1.12.0 due py3.6 not support onnx 1.12.0 * overcome onnx issue on win by import workaround * update onnx>=1.11.0, <1.12.0 * update pipfile onnx>=1.11.0 Co-authored-by: Adrian Boguszewski <adekboguszewski@gmail.com> Co-authored-by: Sun, Xiake <xiake.sun@intel.com> Co-authored-by: Paula Ramos <pjramg@gmail.com>
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.docker/Pipfile

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nest-asyncio = "<=1.5.4"
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nltk = ">=3.6.4"
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nncf = {extras = ["torch", "tf"]}
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onnx = ">=1.11.0"
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openvino-dev = {extras = ["onnx","tensorflow2"], version = "==2022.1.0"}
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ovmsclient = "*"
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paddle2onnx = ">=0.6,<=0.9.6"
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pytube = "*"
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rsa = ">=4.7"
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scikit-learn = ">=0.24.2"
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seaborn = ">=0.11.0"
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setuptools = ">56.0.0"
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supervisor = "==4.1.0"
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tensorflow_datasets = "*"

.docker/Pipfile.lock

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README.md

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| [217-vision-deblur](notebooks/217-vision-deblur/)<br>[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/217-vision-deblur?labpath=notebooks%2F217-vision-deblur%2F217-vision-deblur.ipynb)| Deblur Images with DeblurGAN-v2 | <img src="https://user-images.githubusercontent.com/41332813/158430181-05d07f42-cdb8-4b7a-b7dc-e7f7d9391877.png" width=225> |
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| [218-vehicle-detection-and-recognition](notebooks/218-vehicle-detection-and-recognition/)<br> | Use pre-trained models to detect and recognize vehicles and their attributes with OpenVINO | <img src = "https://user-images.githubusercontent.com/47499836/163544861-fa2ad64b-77df-4c16-b065-79183e8ed964.png" width=225> |
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| [219-knowledge-graphs-conve](notebooks/219-knowledge-graphs-conve/)<br> | Optimize the knowledge graph embeddings model (ConvE) with OpenVINO ||
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| [220-yolov5-accuracy-check-and-quantization](notebooks/220-yolov5-accuracy-check-and-quantization)<br> | Quantize the Ultralytics YOLOv5 model and check accuracy using the OpenVINO POT API | <img src = "https://user-images.githubusercontent.com/44352144/177097174-cfe78939-e946-445e-9fce-d8897417ef8e.png" width=225> |
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| [221-machine-translation](notebooks/221-machine-translation)<br> | Real-time translation from English to German | |
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</details>
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</p>
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README_cn.md

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| [213-question-answering](notebooks/213-question-answering/)<br>[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F213-question-answering%2F213-question-answering.ipynb) | 根据语境回答问题 | <img src="https://user-images.githubusercontent.com/4547501/152571639-ace628b2-e3d2-433e-8c28-9a5546d76a86.gif" width=225> |
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| [216-license-plate-recognition](notebooks/216-license-plate-recognition/)<br> | 在交通中识别中国车牌 | <img src="https://user-images.githubusercontent.com/70456146/162759539-4a0a996f-dabe-40ea-98d6-85b4dce8511d.png" width=225> |
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| [218-vehicle-detection-and-recognition](notebooks/218-vehicle-detection-and-recognition/)<br> | 车辆检测与识别 | <img src = "https://user-images.githubusercontent.com/47499836/163544861-fa2ad64b-77df-4c16-b065-79183e8ed964.png" width=225> |
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| [220-yolov5-accuracy-check-and-quantization](notebooks/220-yolov5-accuracy-check-and-quantization) | 基于POT工具量化Ultralytics Yolov5模型并分析精度 | <img src = "https://user-images.githubusercontent.com/44352144/177097174-cfe78939-e946-445e-9fce-d8897417ef8e.png" width=225> |
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### 模型训练
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