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📚 Jupyter notebook tutorials for OpenVINO™

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# 基于PaddleOCR和PaddleDetection进行工频场强计读数识别 本ISSUE是赛题[【PaddlePaddle Hackathon 4】No.205](https://github.com/PaddlePaddle/community/blob/master/hackthon_4th/%E3%80%90PaddlePaddle%20Hackathon%204%E3%80%91%20%E7%94%9F%E6%80%81%E4%BC%99%E4%BC%B4%E5%BC%80%E6%BA%90%E8%B4%A1%E7%8C%AE%E4%BB%BB%E5%8A%A1%E5%90%88%E9%9B%86.md#task205)的方案设计。 ## 方案目标 工频场强计是用于测量交流电工作频率,以及交流电产生的电场和磁场强度(即高压辐射)的仪器。该仪器多为手持式,类似于[电表读数](https://aistudio.baidu.com/aistudio/projectdetail/3429765?channelType=0&channel=0),对工频场强计图片进行识别能够代替人工抄表,提高工作效率。本方案的目标是识别工频场图像中的工频电磁场数值和单位、以及下方X\Y\Z的数值,结构化输出结果: `[ {"Info_Probe":""}, {"Freq_Set":""}, {"Freq_Main":""}, {"Val_Total":""},{"Val_X":""}, {"Val_Y":""}, {"Val_Z":""}, {"Unit":""}, {"Field":""} ] `。下图展示了两种工频场强计及对应的结构化输出结果。 ## 方案介绍 该项目的推理部分的方案策略为通过PaddleDetection锁定和截取场强计区域,通过PaddleOCR检测区域内文字,并填充对应输出结构体。具体识别流程如下: 1. 通过PaddleDetection中的PPYoloE检测场强计屏幕的位置,并截取屏幕 2. 使用PaddleOCR检测截取区域内的文字 3. 根据文字信息(如文字的内容/文字框的大小等)确定文字对应的属性条目。例如最大的文字框对应的信息为输出结构体中的Val_Total信息。 流程图如下所示: ##...

paddle hackathon

I tried to implement on OpenVINO a Catboost implemented by me, before I had to transform the Catboost to ONNX, and then from ONNX to OpenVINO. When I run the...

enhancement
no_stale
Stale

Hi, Thanks for your work on the notebook. I see that the notebook classifies an entire video as shown in this tutorial: [https://docs.openvino.ai/nightly/notebooks/210-slowfast-video-recognition-with-output.html](url) and the respective notebook. It works on...

According to https://github.com/openvinotoolkit/openvino_notebooks/issues/998, I add a notebook about meter reader. The meter reader recognizes text based on the given layout information and outputs it in a structured format. Summary -...

paddle hackathon

**Describe the bug** Hello, I came across some usage instructions for the qwen model in Jupyter Notebook(254-llm-chatbot), but it seems that there is no specific guide for using qwen 1.8B....

support_request

**Here's a breakdown of what's included:** **_Streamlit Component:_** A user-friendly interface for code input and translated output. **Key Benefits:** 1. Enhanced User Experience: Expands accessibility for German-speaking users. 2. Improved...

**Describe the bug** We are using the [openvino operator](https://github.com/openvinotoolkit/operator) on OCP 4.13 Red Hat Core OS system- based on RHEL 9.2 with Intel Data Center Flex GPU. The notebook custom...

enhancement

Updating Hybrid and Generative AI Conference demo files.