Creating a Python Virtual Environment for OCR Provided that you were able to install Tesseract on your operating system, you can verify that Tesseract is installed by using the tesseract command: $ tesseract -v That said, if you wish to install Tesseract on Windows, we recommend that you follow the official Windows install instructions put together by the Tesseract team. We instead recommend using a Unix-based machine such as Linux/Ubuntu or macOS, both of which are better suited for developing computer vision, deep learning, and OCR projects. These notebooks run on all environments, including macOS, Linux, and Windows. Please note that the PyImageSearch team and I do not officially support Windows, except for customers who use our pre-configured Jupyter/Colab Notebooks, which you can find at PyImageSearch University. The apt-get package manager will automatically install any prerequisite libraries or packages required for Tesseract. Installing Tesseract on Ubuntu 18.04 is easy - all we need to do is utilize apt-get: $ sudo apt install tesseract-ocr Provided that the above command does not exit with an error, you should now have Tesseract installed on your macOS machine. Use the link above to install Homebrew on your system if it is not already installed.įrom there, all you need to do is use the brew command to install Tesseract: $ brew install tesseract Installing the Tesseract OCR engine on macOS is quite simple if you use the Homebrew package manager. Inside this tutorial, you will learn how to install Tesseract on your machine. With that said, let’s install the Tesseract OCR engine on your system! Installing Tesseract The install instructions for Tesseract OCR are fairly stable. The Tesseract OCR engine has existed for over 30 years. From there, you’ll learn how to create a Python virtual environment and then install OpenCV, PyTesseract, and all the other necessary Python libraries you’ll need for OCR, computer vision, and deep learning. In the first part of this tutorial, you will learn how to install the Tesseract OCR engine on your system. OCR Development Environment Configuration Install the necessary Python packages you need to run the examples in this tutorial (and develop OCR projects of your own).Learn how to create a Python virtual environment (a best practice in Python development).Learn how to install the Tesseract OCR engine on your machine.To learn how to configure your development environment, just keep reading. You can start by choosing your own datasets or using our PyimageSearch’s assorted library of useful datasets.īring data in any of 40+ formats to Roboflow, train using any state-of-the-art model architectures, deploy across multiple platforms (API, NVIDIA, browser, iOS, etc), and connect to applications or 3rd party tools. Sign up or Log in to your Roboflow account to access state of the art dataset libaries and revolutionize your computer vision pipeline. Roboflow has free tools for each stage of the computer vision pipeline that will streamline your workflows and supercharge your productivity. It helps in verifying the successful installation and allows for the initial exploration of these OCR tools. Once your machine is configured, we’ll start writing Python code to perform OCR, paving the way for you to develop your own OCR applications.Ī text-image dataset is useful when installing and testing Tesseract and PyTesseract. In this tutorial, we will configure our development environment for OCR.
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