Download Tesseract OCR for free. Commercial quality OCR. A commercial quality OCR engine originally developed at HP between 1985 and 1995. In 1995, this engine was among the top 3 evaluated by UNLV. Virtualenv -p python3 ocrenv. Note: Make sure you have Python version 3 or further installed on your system. Now, activate your environment with the following command in terminal: source ocrenv/bin/activate. Now, you are ready to install OCR and Tesseract, use the commands mentioned below one by one: pip install opencv-python pip install. Tesseract is one of the most powerful open source OCR engine available today. OCR stands for Optical Character Recognition. This is the process of extracting texts from images. For example, consider the following image which has some text in it that has to be extracted out.
TESSA DAM offers all the features you know from Akeneo PAM. However, TESSA DAM also has many other features that simplify and optimize working with your digital assets. For example, TESSA is a full-featured digital asset management solution that allows you to map, control and manage the entire lifecycle (from creation to release) of your assets directly in TESSA. In comparison, for example, the Akeneo PAM primarily offers features only to manage the release of assets in the context of your products. -Akeneo PAM is therefore not a full-featured DAM solution as TESSA is.
Since a picture is worth 1000 words, you should maintain and update assets (such as images and video) just as carefully as any other product data. Since this is not possible with the asset management solution from Akeneo (PAM), it is recommended to use a digital asset management solution, such as TESSA DAM.
Digital asset management with TESSA DAM offers numerous advantages over the Akeneo Enterprise Version integrated asset management solution (PAM). A detailed analysis of your own requirements can help to decide whether the asset management of Akeneo (PAM) is sufficient or which additional functions are necessary in the daily handling of your own digital assets. Should additional functions be necessary, TESSA as a full-featured and fully integrated DAM solution for Akeneo, is an ideal supplement to the Akeneo PIM. Here, TESSA takes over all the functions which the Asset Management (PAM) of Akeneo offers. TESSA DAM also offers many other features that Akeneo can not offer as a PIM system.
- Completely new possibilities of cooperation with suppliers, subsidiaries, partners, team members and external service providers.
- Significantly improved and more transparent communication about an asset. Faster reconciliation and less errors.
- Search and find assets for a product using the integrated full text search for all relevant product data (number, title, description, etc.).
TESSA DAM as a stand-alone solution, fully integrated in Akeneo or both at the same time
TESSA DAM was designed and implemented as an independent software solution right from the start. TESSA DAM can be used completely independently of Akeneo PIM. On the other hand, by using our connectors, TESSA DAM and Akeneo PIM can be optimally connected. You extend Akeneo by the various functions of a fully-featured DAM system. Since we also map all functions of the Akeneo PAM, there is no need to use the Akeneo PAM. Your assets are simply stored centrally in TESSA and are automatically available in Akeneo PIM.
Tessa Ocr Software
Assignment of images and products via Drag&Drop
No need for manually uploading your images and digital assets to Akeneo. With TESSA, you can assign any asset, such as images and documents, directly to your products by drag&drop.
Automatic assignment of images and products
Using freely definable rules, TESSA can automate the assignment of image and media data to your product data. TESSA can read almost any data source (hard disk, network drive, cloud storage, etc.) and automate the assignment of your products digital assets by using rules that have been defined once, such as corresponding file names or folder structures. By this way, several thousand images can be automatically assigned within a very short time.
Asset workflows for more control and optimal quality
Workflows offer the possibility to map your processes optimally in TESSA DAM. They support you and your team in their daily work and ensure that the quality of your data is at the best. For example, you can use your own approval workflows to ensure that only assets that have been approved by responsible persons are published in your channels. Workflows help you to always keep an overview by retracing who has made which changes to what asset.
Comments and remarks
With TESSA you can optimize the collaboration in your team or with external service providers. In addition to workflows, you can also use comment functions to leave notes on any asset and communicate this information to the team. Since this eliminates the need to send and comment on assets and annotations by e-mail, communication paths become shorter and changes are easier to track.
Work in Adobe Photoshop or Adobe InDesign
By connecting TESSA to Adobe Photoshop or InDesign, photographers and graphic designers have perfect access to your assets and product data. Since all data is always stored centrally in TESSA, a graphic designer can edit a product photo directly in Photoshop. After saving this directly in TESSA this is available to all connected channels such as website or online shop. - A manual upload to Akeneo PIM is not necessary and the graphic designer does not even have to leave his usual working environment (Photoshop or InDesign).
The optimal tool for every user
The use of TESSA DAM, Akeneo PIM and possible other connectors provides every user with the optimum tools for daily work. This allows the product manager to work directly with the product data in Akeneo PIM. The graphic designer, on the other hand, can work with the image data directly in TESSA (or via connectors in Photoshop and InDesign). Every user finds the optimal tools for his daily work. - Since both systems are seamlessly connected, the product manager can access all assets and the graphic designer can use all product data, of course.
Duplicate detection
With TESSA DAM you create structure within your assets. TESSA has various mechanisms for duplicate detection. For example, files with the same content and different file names can be reliably detected. But also files with the same name in different file types (e.g. 'test.jpg' and 'test.tif') can be recognized without problems and marked as duplicates.
Automatic keywording and recognition of image content (Google Vision API)
TESSA DAM is able to automatically recognize image content and provide suggestions for appropriate keywords. The Vision API from Google is used to analyze the image content and store appropriate information such as keywords on the image. In addition, TESSA is also able to recognize objects (buildings, monuments, etc.) and texts (OCR) in images and documents.
Any attributes for your assets
With TESSA DAM you can define any attributes for your assets and optimally adapt the system to your needs. In addition to the standard attributes, any other attributes are possible. These can be saved language- and channel-dependent, depending on the type of asset. Some of the most frequently used attributes are e.g.
Automatically rename assets
With TESSA DAM your assets can be renamed automatically. This can be done rule-based during upload and import or alternatively, when rolling out your assets to any channel. For example, you can rename your assets according to criteria such as the supplier's item number, EAN code, serial numbering with consecutive numbers or product names for SEO friendly use.
Web portals, publications and downloads
With TESSA, you can distribute and email your digital assets with just a few clicks. There are several ways to achieve this, all independent of Akeneo PIM. You can send your assets by e-mail via a link or create a download portal for your customers. - Password protection, time control and file conversion are also fully integrated.
Monday, 24 August, 2020
Optical character recognition (OCR) is the conversion of images containing text to machine-encoded text. A popular tool for this is the open source project Tesseract. Tesseract can be used as standalone application from the command line. Alternatively it can be integrated into applications using its C++ API. For other programming languages various wrapper APIs are available. In this post we will use the Java Wrapper Tess4J.
Getting started
We start with adding the Tess4J maven dependency to our project:
Next we need to make sure the native libraries required by Tess4j are accessible from our application. Tess4J jar files ship with native libraries included. However, they need to be extracted before they can be loaded. We can do this programmatically using a Tess4J utility method:
With LoadLibs.extractTessResources(..) we can extract resources from the jar file to a local temp directory. Note that the argument (here win32-x86-64) depends on the system you are using. You can see available options by looking into the Tess4J jar file. We can instruct Java to load native libraries from the temp directory by setting the Java system property java.library.path.
Other options to provide the libraries might be installing Tesseract on your system. If you do not want to change the java.library.path property you can also manually load the libraries using System.load(..).
Next we need to provide language dependent data files to Tesseract. These data files contain trained models for Tesseracts LSTM OCR engine and can be downloaded from GitHub. For example, for detecting german text we have to download deu.traineddata (deu is the ISO 3166-1-alpha-3 country code for Germany). We place one or more downloaded data files in the resources/data directory.
Detecting Text
Now we are ready to use Tesseract within our Java application. The following snippet shows a minimal example:
First we create a new Tesseract instance. We set the language we want to recognize (here: german). With setOcrEngineMode(1) we tell Tesseract to use the LSTM OCR engine.
Next we set the data directory with setDatapath(..) to the directory containing our downloaded LSTM models (here: resources/data).
Finally we load an example image from the classpath and use the doOCR(..) method to perform character recognition. As a result we get a String containing detected characters.
For example, feeding Tesseract with this photo from the German wikipedia OCR article might produce the following text output.
Text output:
Summary
Tessa Ocr Free
Tessa Ocr Reader
Tesseract is a popular open source project for OCR. With Tess4J we can access the Tesseract API in Java. A little bit of set up is required for loading native libraries and downloading Tesseracts LSTM data. After that it is quite easy to perform OCR in Java. If you are not happy with the recognized text it is a good idea to have a look at the Improving the quality of the output section of the Tesseract documentation.
Tessa Ocr Reader
You can find the source code for the shown example on GitHub.
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