Based on our record, Tesseract seems to be a lot more popular than Supervisely. While we know about 75 links to Tesseract, we've tracked only 6 mentions of Supervisely. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Many of the OCR services are based on the free, open-source Tesseract OCR, but don’t expose all of the options. If you’re handy with shell scripts or Python, you can probably get better performance by hand-tuning options for your particular images. For example, if I recall there are page segmentation options to tell Tesseract to expect multi-column text. That alone might get you better performance than the... - Source: Hacker News / 10 days ago
If you want to learn more visit the complete tesseract documentation. - Source: dev.to / about 1 month ago
AI copilots: Copilots powered by various LLMs like Pieces Copilot can leverage computer vision technologies for inputs beyond text and code. For example, optical character recognition software at Pieces uses Tesseract as its main OCR code engine, extended with bicubic upsampling. Pieces then uses edge-ML models to auto-correct any potential defects in the resulting code/text, which users can input as prompts to... - Source: dev.to / about 1 month ago
You will also need to install the Tesseract OCR engine, which can be downloaded and installed from the following link: https://github.com/tesseract-ocr/tesseract. - Source: dev.to / 4 months ago
Tesseract is an open-source OCR engine developed by Google. It is highly accurate and supports multiple languages. This library will do all the heavy lifting for us. We'll use it in this tutorial to quickly read the text in some images. - Source: dev.to / 8 months ago
Another annotation tool that integrates prediction and training within the application is supervisely supervisely.com., unfortunately it's pretty expensive unless you are satisfied with the community version. I saw that they have an integration for owl-vit, which might be helpful for annotation of animals. https://ecosystem.supervisely.com/apps/serve-owl-vit. Source: about 1 year ago
Hello world. This tutorial is a gentle introduction to building modern text recognition system using deep learning in 15 minutes. It will teach you the main ideas of how to use Keras and Supervisely for this problem. This guide is for anyone who is interested in using Deep Learning for text recognition in images but has no idea where to start. - Source: dev.to / over 1 year ago
If they were videos, I would have suggested trying supervise.ly as it has a very good tracking functionality. Source: almost 2 years ago
Hi, I'm exactly in the same boat like you are. I looked around for a while and the better solutions I found was supervise.ly and CVAT for video annotation. The pricetag on supervisely is pretty high, so I analyzed CVAT for a couple days and was positively surprised. Source: almost 2 years ago
Under the WPI Photo Ambum section of the page for FRC field photos (https://www.firstinspires.org/robotics/frc/playing-field#WPIPhotos), they have a section of machine learning imagery. However, this link goes to supervise.ly, the website they use for machine learning. I created an account to attempt to download the images, however, whenever I try to 'clone' the project, it stalls at 0% and gives me an error... Source: almost 2 years ago
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