This Django project deployed on PythonAnywhere offers a comprehensive solution for digitizing catalogs using multiple modes of input. Users can input text, text in Indic languages, voice recordings in multiple languages, and utilize optical character recognition (OCR) for images. The system also supports a combination of image-text and audio modes for enhanced data capture. Additionally, users can easily view all digitized records through a user-friendly interface, making it a versatile tool for efficient catalog management.
- 14/03/24 - The project has been deployed as fully functional website at [https://samte.pythonanywhere.com/] with Python Anywhere
In the text mode of this catalog digitization system, users input SKU ID, product name, price, count, and attach an image. The system then processes this information to digitize the catalog, ensuring efficient and accurate conversion of the data for catalog management.
The text Indic mode supports input in multiple languages, including Marathi, Tamil, and Hindi. This mode allows healthcare providers to input patient data in their preferred language, making the system more accessible and user-friendly.
The voice mode enables users to input data where the system read aloud the input fields through voice commands in English languages. This mode is ideal for healthcare providers who prefer to use voice commands or who have limited access to manual data entry or image recognition technology.
The voice Indic feature reads aloud the input fields in Indic languages, providing better accessibility for healthcare providers who are visually impaired or have difficulty reading text.
Utilizes Optical Character Recognition (OCR) technology to extract data from images, making it easier to digitize physical records.
Supports a combination of all five modes, providing flexibility for users to choose the best input method based on their needs.
The view-all-records feature enables healthcare providers to access and view all patient health records in one place. This feature is ideal for healthcare providers who want to access patient data quickly and efficiently.
1.Multimode Input: The project allows users to input data in various formats, including text, voice recordings, and images, making it a versatile tool for digitizing catalogs.
2.Multilingual Support: It supports text and voice inputs in multiple languages, including Indic languages, which broadens its scope of use and makes it accessible to a diverse range of users.
3.Optical Character Recognition (OCR): The system is equipped with OCR technology for processing images, enabling the conversion of scanned documents, PDF files, or images into editable and searchable data.
4.Combination Input Modes: The project offers a unique feature of combining image-text and audio modes for enhanced data capture, providing a more comprehensive and flexible digitization solution.
5.User-Friendly Interface for Record Viewing: The project provides a user-friendly interface where users can easily view all digitized records, making catalog management more efficient and convenient.
6.Deployment on PythonAnywhere: The Django project is deployed on PythonAnywhere, ensuring easy access and reliable performance. This makes it a convenient and efficient tool for catalog management.
To install the Comprehensive Digital Health Record System, follow these steps:
- Clone the repository onto your local machine using Git.
- Install the necessary dependencies, including Python, Django, and SQLite.
- Set up the database and configure the settings.py file.
- Run the migrations to create the database tables.
- Start the Django development server.
- Access the system through a web browser.
To use the Django-Powered-Catalog-Digitalization System, follow these steps:
- Access the Django-powered catalog digitization system.
- Choose the text mode input option to enter product details like SKU ID, product name, price, count, and upload images.
- Submit the data for processing and catalog digitization.
- Navigate the user interface to manage and view digitized records.
- Utilize the OCR feature for image processing to extract data accurately from uploaded images.
- Use the view-all-records feature to access all patient health records in one place.
Language: Python 3.10.12
Django==5.0.2: The Django web framework.
numpy==1.26.4: The NumPy library for scientific computing.
pandas==2.2.1: The Pandas library for data manipulation and analysis.
pillow==10.2.0: The Pillow library for image processing.
pytz==2024.1: The PyTZ library for handling time zones.
requests==2.31.0: The Requests library for making HTTP requests.
If you have any questions, please feel free to contact me at [[email protected]].
This project is licensed under the Apache 2.0 License.
If you find this project interesting or helpful, don't hesitate to share with your community! Let's learn and grow together!
In this project, we’ve developed a robust solution for Digitizing product catalogues. The model, a beacon of performance, awaits those go into the beautiful world of Python.