Follow these tutorials and you’ll have enough knowledge to start applying Deep Learning to your own projects. For Greek and Serbian Cyrillic, the legacy OCR API is used. How to apply Azure OCR API with Request library on local images?Nowadays, each product contains a barcode on its packaging, which can be analyzed or read with the help of the computer vision technique OCR. Ingest the structure data and create a searchable repository, thereby making it easier for. We will use the OCR feature of Computer Vision to detect the printed text in an image. We’ve coded an algorithm using Computer Vision to find the position of information in the tables using thresholding, dilation, and contour detection techniques. Once this is done, the connectors will be available to integrate the Computer Vision API in Logic Apps. PyTesseract One of the first applications of Computer Vision was Optical Character Recognition (OCR). CV applications detect edges first and then collect other information. Computer Vision projects for all experience levels Beginner level Computer Vision projects . Using AI technologies such as computer vision, Optical Character Recognition (OCR), Natural Language Processing (NLP), and machine/deep learning, the extracted data can. Elevate your computer vision projects. Understand and implement Histogram of Oriented Gradients (HOG) algorithm. That's where Optical Character Recognition, or OCR, steps in. Inside PyImageSearch University you'll find: ✓ 81 courses on essential computer vision, deep learning, and OpenCV topics ✓ 81 Certificates of Completion ✓ 109+. Clone the repository for this course. 8 A teacher researches the length of time students spend playing computer games each day. It also includes support for handwritten OCR in English, digits, and currency symbols from images and multi. Use natural language to fetch visual content in images and videos without needing metadata or location, generate automatic and detailed descriptions of images using the model’s knowledge of the world, and use a verbal description to. , into structured data, using computer vision (CV), natural language processing (NLP), and deep learning (DL) techniques. It also has other features like estimating dominant and accent colors, categorizing. It was invented during World War I, when Israeli scientist Emanuel Goldberg created a machine that could read characters and convert them into telegraph code. The OCR service can read visible text in an image and convert it to a character stream. Understand and implement convolutional neural network (CNN) related computer vision approaches. Deep Learning. The activity enables you to select which OCR engine you want to use for scraping the text in the target application. For example, it can be used to determine if an image contains mature content, or it can be used to find all the faces in an image. We also use OpenCV, which is a widely used computer vision library for Non-Maximum Suppression (NMS) and perspective transformation (we’ll expand on this later) to post-process detection results. The newer endpoint ( /recognizeText) has better recognition capabilities, but currently only supports English. LLaVA, and Qwen-VL demonstrate capabilities to solve a wide range of vision problems, from OCR to VQA. For example, it can be used to determine if an image contains mature content, or it can be used to find all the faces in an image. As Reddit users were quick to point out, utilizing computer vision to recognize digits on a thermostat tends to overcomplicate the problem — a simple data logging thermometer would give much more reliable results with a fraction of the effort. It is widely used as a form of data entry from printed paper. ) or from. Azure AI Vision is a unified service that offers innovative computer vision capabilities. In this article. First, the software classifies images of common documents by their structure (for example, passports, birth certificates,. Contact Sales. The script takes scanned PDF or image as input and generates a corresponding searchable PDF document using Form Recognizer which adds a searchable layer to the PDF and enables you to search, copy, paste and access the text within the PDF. py file and insert the following code: # import the necessary packages from imutils. The version of the OCR model leverage to extract the text information from the. INPUT_VIDEO:. The origin of OCR dates back to the 1950s, when David Shepard founded Intelligent Machines Research Corporation (IMRC), the world’s first supplier of OCR systems operated by private companies for converting. object_detection import non_max_suppression import numpy as np import pytesseract import argparse import cv2. 2. 1 Answer. 2) The Computer Vision API provides state-of-the-art algorithms to process images and return information. To accomplish this, we broke our image processing pipeline into 4. Computer Vision service provided by Azure provides 3000 tags, 86 categories, and 10,000 objects. Azure Cognitive Services Computer Vision SDK for Python. Implementing our OpenCV OCR algorithm. Computer Vision API (v1. 0) The Computer Vision API provides state-of-the-art algorithms to process images and return information. ; End Date - The end date of the range selection. Choose between free and standard pricing categories to get started. With OCR, it also absorbs the numbers on the packaging to better deliver. e. Machine vision can be used to decode linear, stacked, and 2D symbologies. Computer Vision algorithms analyze the content of an image in different ways, depending on the visual features you're interested in. This question is in a collective: a subcommunity defined by tags with relevant content and experts. For example, it can determine whether an image contains adult content, find specific brands or objects, or find human faces. McCrodan. My brand new book, OCR with OpenCV, Tesseract, and Python, is for developers, students, researchers, and hobbyists just like you who want to learn how to successfully apply Optical Character Recognition to your work, research, and projects. It. When I pass a specific image into the API call it doesn't detect any words. We detect blurry frames and lighting conditions and utilize usable frames for our character recognition pipeline. Large models have recently played a dominant role in natural language processing and multimodal vision-language learning. This entry was posted in Computer Vision, OCR and tagged CNN, CTC, keras, LSTM, ocr, python, RNN, text recognition on 29 May 2019 by kang & atul. Optical Character Recognition (OCR) is the process that converts an image of text into a machine-readable text format. Computer Vision API (v3. This paper introduces the off-road motorcycle Racer number Dataset (RnD), a new challenging dataset for optical character recognition (OCR) research. To apply our bank check OCR algorithm, make sure you use the “Downloads” section of this blog post to download the source code + example image. Requirements. Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. Learn the basics of computer vision by applying a typical workflow—tracking-by-detection—to video of turtles crawling towards the sea. 全角文字も結構正確に読み取れていました。 Understand pricing for your cloud solution. Activities `${date:format=yyyy-MM-dd. This growth is driven by rapid digitization of business processes using OCR to reduce their labor costs and to save precious man hours. OCR (Optical Character Recognition) is the process of detecting and extracting text in images through Computer Vision. Replace the following lines in the sample Python code. CognitiveServices. Detection of text from document images enables Natural Language Processing algorithms to decipher the text and make sense of what the document conveys. Bring your IDP to 99% with intelligent document processing. View on calculator. Description: Georgia Tech has also put together an effective program for beginners to learn about Computer Vision. 2 Create computer vision service by selecting subscription, creating a resource group (just a container to bind the resources), location and. This article is the reference documentation for the OCR skill. Use of computer vision in IronOCR will determine where text regions exists and then use Tesseract to attempt to read. The UiPath Documentation Portal - the home of all our valuable information. A license plate recognizer is another idea for a computer vision project using OCR. References. In this guide, you'll learn how to call the v3. This guide assumes you have already create a Vision resource and obtained a key and endpoint URL. Via the portal, it’s very easy to create a new Computer Vision service. Reference; Feedback. Microsoft Azure Collective See more. . The Azure AI Vision Image Analysis service can extract a wide variety of visual features from your images. Optical Character Recognition (OCR) – The 2024 Guide. 0 and Keras for Computer Vision Deep Learning tasks. Intelligent Document Processing (IDP) is a software solution that captures, transforms, and processes data from documents (e. Give your apps the ability to analyze images, read text, and detect faces with prebuilt image tagging, text extraction with optical character recognition (OCR), and responsible facial recognition. We will use the OCR feature of Computer Vision to detect the printed text in an image. Firstly, note that there are two different APIs for text recognition in Microsoft Cognitive Services. Desktop flows provide a wide variety of Microsoft cognitive actions that allow you to integrate this functionality into your desktop flows. Consider joining our Discord Server where we can personally help you. Copy code below and create a Python script on your local machine. As you can see, there is tremendous value in using an AI-based solution that incorporates OCR. RepeatForever - Enables you to perpetually repeat this activity. We then applied our basic OCR script to three example images. 2) The Computer Vision API provides state-of-the-art algorithms to process images and return information. OCR_CLASSES: a list of the classes we want our OCR model to read from, in our case just license-plate. GetModel. It is for this purpose that a computer vision service has been developed : Optical Character Recognition (OCR), commonly known as OCR. A varied dataset of text images is fundamental for getting started with EasyOCR. Azure OCR is an excellent tool allowing to extract text from an image by API calls. OpenCV in python helps to process an image and apply various functions like resizing image, pixel manipulations, object detection, etc. Initial OCR Results Feeding the image to the Tesseract 4. The following example extracts text from the entire specified image. In the Body of the Activity. We discussed how, unicorn startup, Instabase is using Azure Computer Vision which includes Optical Character Recognition (OCR) capabilities to extract data from documents or images. OCR, or optical character recognition, is one of the earliest addressed computer vision tasks, since in some aspects it does not require deep learning. Join me in computer vision mastery. py file and insert the following code: # import the necessary packages from imutils. Please refer to this article to configure and use the Azure Computer Vision OCR services. The neural network is. This is useful for images that contain a lot of noise, images with text in many different places, and images where text is warped. Image Denoising using Auto Encoders: With the evolution of Deep Learning in Computer Vision, there has been a lot of research into image enhancement with Deep Neural Networks like removing noises. The workflow contains the following activities: Open Browser - Opens in Internet Explorer. Using Microsoft Cognitive Services to perform OCR on images. Easy OCR. Combine vision and language in an AI model with the latest vision AI model in Azure Cognitive Services. It also has other features like estimating dominant and accent colors, categorizing. Do not provide the language code as the parameter unless you are sure about the language and want to force the service to apply only the relevant model. Press the Create button at the. Use computer vision to separate original image into images based on text regions with FindMultipleTextRegions. Download C# library to use OCR with Computer Vision. Here you’ll learn how to successfully and confidently apply computer vision to your work, research, and projects. For example, it can be used to determine if an image contains mature content, or it can be used to find all the faces in an image. There are many standard deep learning approaches to the problem of text recognition. Bethany, we'll go to you, my friend. The Overflow Blog The AI assistant trained on your company’s data. Optical Character Recognition or Optical Character Reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo (for example the text on signs and billboards in a landscape photo, license plates in cars. In project configuration window, name your project and select Next. Find here everything you need to guide you in your automation journey in the UiPath ecosystem, from complex installation guides to quick tutorials, to practical business examples and automation best practices. Yuan's output is from the OCR API which has broader language coverage, whereas Tony's output shows that he's calling the newer and improved Read API. 2 の一般提供が 2021 年 4 月に開始されました。このアップデートには、73 言語で利用可能な OCR (Read) が含まれており、日本語の OCR を Read API を使って利用することができるようになりました. However, as we discovered in a previous tutorial, sometimes Tesseract needs a bit of help before we can actually OCR the text. Build frictionless customer experiences, optimize manufacturing processes, accelerate digital marketing campaigns, and more. Join me in computer vision mastery. Azure AI Services offers many pricing options for the Computer Vision API. The OCR supports extracting printed and handwritten text from images and documents; mixed languages; digits; currency symbols. Machine-learning-based OCR techniques allow you to extract printed or handwritten text from images such as posters, street signs and product labels, as well as from documents like articles, reports, forms, and invoices. Computer Vision Read (OCR) API previews support for Simplified Chinese and Japanese and extends to on-premise with new docker containers. 2 in Azure AI services. 1 release implemented GPU image processing to speed up image processing – 3. Optical character recognition or optical character reader (OCR) is a computer vision technique that converts any kind of written or printed text from an image into a machine-readable format. Figure 4: Specifying the locations in a document (i. Start with prebuilt models or create custom models tailored. You can master Computer Vision, Deep Learning, and OpenCV - PyImageSearch. You can also extract metadata about the image, such as. See Extract text from images for usage instructions. Form Recognizer is an advanced version of OCR. Microsoft Cognitive Services API OCRs the image line-by-line, resulting in the text “Old Town Rd” and “All Way” to be OCR’d as a single line. Document Digitization. Dr. Here you’ll learn how to successfully and confidently apply computer vision to your work, research, and projects. Run the dockerfile. Here you’ll learn how to successfully and confidently apply computer vision to your work, research, and projects. Depending on what you’re trying to build with computer vision and OCR, you may want to spend a few weeks to a few months just familiarizing yourself with NLP — that knowledge will better help. It will simply create a blank new Ionic 4 Project named IonVision. 2) The Computer Vision API provides state-of-the-art algorithms to process images and return information. You need to enable JavaScript to run this app. 0) The Computer Vision API provides state-of-the-art algorithms to process images and return information. To do this, I used Azure storage, Cosmos DB, Logic Apps, and computer vision. Why Computer Vision. So today we're talking about computer vision. If you’re new to computer vision, this project is a great start. Current Visual Document Understanding (VDU) methods outsource the task of reading text to off-the-shelf Optical Character Recognition (OCR) engines and focus. Our basic OCR script worked for the first two but. Optical Character Recognition (OCR), the method of converting handwritten/printed texts into machine-encoded text, has always been a major area of research in computer vision due to its numerous applications across various domains -- Banks use OCR to compare statements; Governments use OCR for survey feedback. 2) The Computer Vision API provides state-of-the-art algorithms to process images and return information. Using this method, we could accept images of documents that had been “damaged,” including rips, tears, stains, crinkles, folds, etc. We are using Tesseract Library to do the OCR. IronOCR utilizes OpenCV to use Computer Vision to detect areas where text exists in an image. This feature will identify and tag the content of an image, give a written description, and give you confidence ratings on the results. If you need help learning computer vision and deep learning, I suggest you refer to my full catalog of books and courses — they have helped tens of thousands of. Search for “Computer Vision” on Azure Portal. Eye irritation (Dry eyes, itchy eyes, red eyes) Blurred vision. It uses a combination of text detection model and a text recognition model as an OCR pipeline to. Updated on Sep 10, 2020. 0) The Computer Vision API provides state-of-the-art algorithms to process images and return information. Next, the OCR engine searches for regions that contain text in the image. 0 client library. 0 has been released in public preview. Computer Vision API (v1. A varied dataset of text images is fundamental for getting started with EasyOCR. To accomplish this part of the project I planned to use Microsoft Cognitive Service Computer Vision API. We’ll use traditional computer vision techniques to extract information from the scanned tables. Deep Learning; Dlib Library; Embedded/IoT and Computer Vision. Computer Vision Image Analysis API is part of Microsoft Azure Cognitive Service offering. Advanced systems capable of producing a high degree of accuracy for most fonts are now common, and with support for a variety of image file format. In factory. 2. Computer Vision is Microsoft Azure’s OCR tool. Optical Character Recognition (OCR) is the process of detecting and reading text in images through computer vision. It uses the. Implementing our OpenCV OCR algorithm. It also has other features like estimating dominant and accent colors, categorizing. With the help of information extraction techniques. These samples demonstrate how to use the Computer Vision client library for C# to. Computer Vision API (v2. This question is in a collective: a subcommunity defined by tags with relevant content and experts. We have already created a class named AzureOcrEngine. OpenCV is the most popular library for computer vision. We are now ready to perform text recognition with OpenCV! Open up the text_recognition. If you need help learning computer vision and deep learning, I suggest you refer to my full catalog of. The older endpoint ( /ocr) has broader language coverage. The Microsoft cognitive computer vision - Optical character recognition (OCR) action allows you to extract printed or handwritten text from images, such as photos of street signs and products, as well as from documents—invoices, bills,. One of the things I have to accomplish is to extract the text from the images that are being uploaded to the storage. You can use Computer Vision in your application to: Analyze images for. However, you can use OCR to convert the image into. Computer Vision. We will use the OCR feature of Computer Vision to detect the printed text in an image. Computer Vision is a field of study that deals with algorithms and techniques that enable computers to process and interact with the visual world. The Optical character recognition (OCR) skill recognizes printed and handwritten text in image files. In this post we will take you behind the scenes on how we built a state-of-the-art Optical Character Recognition (OCR) pipeline for our mobile document scanner. OCR is one of the most useful applications of computer vision. g. As it still has areas to be improved, research in OCR has continued. Refer to the image shown below. The Computer Vision activities contain refactored fundamental UI Automation activities such as Click, Type Into, or Get Text. After creating computer vision. OCR & Read – Both features apply optical character recognition (OCR) technology for detecting text in an image, which can be extracted for multiple purposes. Build the dockerfile. UIAutomation. I want the output as a string and not JSON tree. TimK (Tim Kok) December 20, 2019, 9:19am 2. Use Form Recognizer to parse historical documents. 0 REST API offers the ability to extract printed or handwritten. OpenCV4 in detail, covering all major concepts with lots of example code. In this comprehensive course, you'll learn everything you need to know to master computer vision and deep learning with Python and OpenCV. OCR & Read—Both features apply optical character recognition (OCR) technology for detecting text in an image, which can be extracted for multiple purposes. , into structured data, using computer vision (CV), natural language processing (NLP), and deep learning (DL) techniques. 実際に Microsoft Azure Computer Vision で OCR を行ってみて. For industry-specific use cases, developers can automatically. WaitVisible - When this check box is selected, the activity waits for the specified UI element to be visible. Overview. To install it, open the command prompt and execute the command “pip install opencv-python“. CV applications detect edges first and then collect other information. Learn to use PyTorch, TensorFlow 2. Custom Vision consists of a training API and prediction API. read_in_stream ( image=image_stream, mode="Printed",. As you can see, there is tremendous value in using an AI-based solution that incorporates OCR. Computer vision utilises OCR to retrieve the information but then uses that along with AI and various methods in order to automatically identify fields / information from that image. Optical character recognition (OCR) is sometimes referred to as text recognition. Microsoft Computer Vision OCR. Two of the most common data ingestion engines are optical character recognition (OCR) and cognitive machine reading (CMR). OCR electronically converts printed or handwritten text image into a format that machines can recognize. From there, execute the following command: $ python bank_check_ocr. Computer Vision Toolbox provides algorithms, functions, and apps for designing and testing computer vision, 3D vision, and video processing systems. Jul 18, 2023OCR is a field of research in pattern recognition, artificial intelligence and computer vision . Computer Vision projects for all experience levels Beginner level Computer Vision projects . When will this legacy API be retiring (endpoints become inactive)? a) When in 2023 will it be available in GA? b) Will legacy OCR API be available till then?Computer Vision API (v3. Azure provides sample jupyter. (a) ) Tick ( one box to identify the data type you would choose to store the data and. Azure AI Services Vision Install Azure AI Vision 3. g. Utilize FindTextRegion method to auto detect text regions. It helps the OCR system to handle a wide range of text styles, fonts, and orientations, enhancing the system’s overall. About this video. The OCR for the handwritten texts is also available, but yet. Computer Vision API Account. Azure AI Vision Image Analysis 4. UiPath Document Understanding and UiPath Computer Vision tools go far beyond basic OCR, enabling rapid and reliable automation with enterprise scalability—which allows you to unlock the full value of your. Steps to perform OCR with Azure Computer Vision. Azure AI Services Vision Install Azure AI Vision 3. Computer Vision API (v3. It detects objects and faces out of the box, and further offers an OCR functionality to find written text in images (such as street signs). To download the source code to this post. OCR or Optical Character Recognition is also referred to as text recognition or text extraction. Read API multipage PDF processing. That can put a real strain on your eyes. Here are some broad categories of vision APIs: Computer Vision provides advanced algorithms that process images and return information based on the visual features you're interested in. Computer Vision is an. Computer vision and image understanding in machine learning is the process of teaching computers to make sense of digital images. The Computer Vision service provides pre-built, advanced algorithms that process and analyze images and extract text from photos and documents (Optical Character Recognition, OCR). 0 has been released in public preview. It also has other features like estimating dominant and accent colors, categorizing. 1. Neck aches. OCR is classified into: (i) offline text recognition, and (ii) online text recognition. Here you’ll learn how to successfully and confidently apply computer vision to your work, research, and projects. An online course offered by Georgia Tech on Udacity. Creating a Computer Vision Resource. 96 FollowersUse Computer Vision API to automatically index scanned images of lost property. Inside PyImageSearch University you'll find: ✓ 81 courses on essential computer vision, deep learning, and OpenCV topics ✓ 81 Certificates of Completion ✓ 109+ hours of on. The Overflow Blog The AI assistant trained on. 0 Read OCR (preview)? The new Computer Vision Image Analysis 4. The 165 revised full papers presented were carefully reviewed and selected from 412 submissions. In this tutorial, you will focus on using the Vision API with Python. On the other hand, Azure Computer Vision provides three distinct features. OCR & Read – Both features apply optical character recognition (OCR) technology for detecting text in an image, which can be extracted for multiple purposes. Azure. The service also provides higher-level AI functionality. Download. 1. Give your apps the ability to analyze images, read text, and detect faces with prebuilt image tagging, text extraction with optical character recognition (OCR), and responsible facial recognition. To start, we need to accept an input image containing a table, spreadsheet, etc. And somebody put up a good list of examples for using all the Azure OCR functions with local images. OCR_CLASSES: a list of the classes we want our OCR model to read from, in our case just license-plate. The most used technique is OCR. Added to estimate. Optical Character Recognition is a detailed process that helps extract text from images using NLP. open source computer vision library, OpenCV and the T esseract OCR engine. For example, it can be used to determine if an image contains mature content, or it can be used to find all the faces in an image. An OCR skill uses the machine learning models provided by Azure AI Vision API v3. Many existing traditional OCR solutions already use forms of computer vision. Join me in computer vision mastery. You can master Computer Vision, Deep Learning, and OpenCV - PyImageSearch. Google Cloud Vision is easy to recommend to anyone with OCR services in their system. Right side - The Type Into activity writes "Example" in the First Name field. The following figure illustrates the high-level. How does the OCR service process the data? The following diagram illustrates how your data is processed. It also has other features like estimating dominant and accent colors, categorizing. OCR software includes paying project administration fees but ICR technology is fully automated;. Today, we'll explore optical character recognition (OCR)—the process of using computer vision models to locate and identify text in an image––and gain an in-depth understanding of some of the common deep-learning-based OCR libraries and their model architectures. Checkbox Detection. Customers use it in diverse scenarios on the cloud and within their networks to solve the challenges listed in the previous section. Understand and implement Viola-Jones algorithm. 0. This kind of processing is often referred to as optical character recognition (OCR). The table below shows an example comparing the Computer Vision API and Human OCR for the page shown in Figure 5. OCR technology: Optical Character Recognition technology allows you convert PDF document to the editable Excel file very accuracy. The Cognitive services API will not be able to locate an image via the URL of a file on your local machine. A dataset comprising images with embedded text is necessary for understanding the EAST Text Detector. Essentially, a still from the camera stream would be taken when the user pressed the 'capture' button and then Tesseract would perform the OCR on it. Anchor Base - Identifies the target field and writes the sample text: Left side - The Find Element activity identifies the First Name field. 1 REST API. Gaming. Tool is useful in the process of Document Verification & KYC for Banks. There are numerous ways computer vision can be configured. The only issue is that the OCR has detected the leftmost numeral as a '6' instead of a '0'. We allow you to manage your training data securely and simply. Example of Object Detection, a typical image recognition task performed by Computer Vision APIs 3. CosmosDB will be used to store the JSON documents returned by the COmputer Vision OCR process. Azure AI Vision Image Analysis 4. ; Select - Select single dates or periods of time. OpenCV’s EAST text detector is a deep learning model, based on a novel architecture and training pattern. The fundamental advantage of OCR technology is that it makes text searches, editing, and storage simple, which simplifies data entry. The OCR service is easy to use from any programming language and produces reliable results quickly and safely. You'll learn the different ways you can configure the behavior of this API to meet your needs. Here are some broad categories of vision APIs: Computer Vision provides advanced algorithms that process images and return information based on the visual features you're interested in. Azure AI Vision is a unified service that offers innovative computer vision capabilities. This tutorial will explore this idea more, demonstrating that. Activities. Figure 4: The Google Cloud Vision API OCRs our street signs but, by. Copy the key and endpoint to a temporary location to use later on. About this codelab. 1. It provides four services: OCR, Face service, Image Analysis, and Spatial Analysis. Machine-learning-based OCR techniques allow you to extract printed or. The OCR API in Azure Computer vision service is used to scan newspapers and magazines. days 0. Through OCR, you can extract text from photos or pictures containing alphanumeric text, such as the word "STOP" in a stop sign. An OCR Engine is used in the Digitization component, to identify text in a file, when native content is not available. Today Dr. An Azure Storage resource - Create one. AWS Textract and GCP Vision remain as the top-2 products in the benchmark, but ABBYY FineReader also performs very well (99. Steps to Use OCR With Computer Vision. Hands On Tutorials----Follow. Q31. The Computer Vision service provides developers with access to advanced algorithms for processing images and returning information. ; Target. It also has other features like estimating dominant and accent colors, categorizing. 0 (public preview) Image Analysis 4. Select Review + create to accept the remaining default options, then validate and create the account. These APIs work out of the box and require minimal expertise in machine learning, but have limited. Install OCR Language Data Files. Vision Studio is a set of UI-based tools that lets you explore, build, and integrate features from Azure AI Vision. An “Add New Item” dialog box will open, select “Visual C#” from the left panel, then select “Razor Component” from the templates panel, put the name as OCR.