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2020-05-19
Model Image Text Feature: Transform Your Visual Content
The Model Image Text feature allows you to create dynamic visual content by combining images and relevant text seamlessly. This tool is designed with user-friendly functionality, making it perfect for marketers, educators, and creatives alike.
Key Features
Intuitive interface for quick content creation
Customizable text overlay options for better engagement
Support for various image formats to suit your needs
Instant preview to see your results in real-time
Compatible with multiple platforms for broad application
Potential Use Cases and Benefits
Enhance marketing campaigns with eye-catching visuals
Create educational materials that are more engaging and informative
Produce social media posts that attract higher interaction rates
Develop presentations that combine visuals and text efficiently
Design product showcases that clearly highlight features and benefits
This feature solves the problem of creating engaging visual content swiftly and easily. By integrating text directly onto images, you can communicate your message more effectively, capture attention quickly, and increase engagement across your various platforms. Streamline your content creation process and elevate your projects with the Model Image Text feature.
For pdfFiller’s FAQs
Below is a list of the most common customer questions. If you can’t find an answer to your question, please don’t hesitate to reach out to us.
What if I have more questions?
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How can I read text from an image?
You can capture text from a scanned image, upload your image file from your computer, or take a screenshot on your desktop. Then simply right-click on the image, and select Grab Text. The text from your scanned PDF can then be copied and pasted into other programs and applications.
Which algorithm is used to detect text in images?
OpenCV Text Detection (EAST text detector) In this tutorial you will learn how to use OpenCV to detect text in natural scene images using the EAST text detector. OpenCV's EAST text detector is a deep learning model, based on a novel architecture and training pattern.
How can I extract text from an image?
Visit OCR. Space's official website.
Click Choose File or paste the URL of the image. ...
Select the extract mode you need and click Start OCR!
When the process is done, click Download to save the extracted text to your computer's hard drive.
How do I extract text from a picture in Word?
Right-click any of the images, and then do one of the following: Click Copy Text from this Page of the Printout to copy text from only the currently selected image (page). ...
Click where you'd like to paste the copied text, and then press Ctrl+V.
Can Google read text in images?
Google Can Read Embedded Text in Images. Yes, Google can read embedded text in images, and it's doing it very well. ... Besides, optic character recognition (OCR) technologies are already used on a large scale, mostly by Google itself for scanning books in the Google Books service.
What is East text detector?
OpenCV Text Detection (EAST text detector) ... OpenCV's EAST text detector is a deep learning model, based on a novel architecture and training pattern. It is capable of (1) running at near real-time at 13 FPS on 720p images and (2) obtains state-of-the-art text detection accuracy.
How does OCR algorithm work?
Optical character recognition, or OCR, is a method of converting a scanned image into text. ... The computer does not recognize any “words” on the image. This is what OCR does. OCR looks at each line of the image and attempts to determine if the black and white dots represent a particular letter or number.
Which algorithm is used for OCR?
The tesseract algorithm is available on Google Code, and is one of the best open source OCR out there.
How is OCR accuracy calculated?
Measuring OCR accuracy is done by taking the output of an OCR run for an image and comparing it to the original version of the same text. You can then either count how many characters were detected correctly (character level accuracy), or count how many words were recognized correctly (word level accuracy).
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