Based on our record, Amazon Rekognition should be more popular than wikidPad. It has been mentiond 33 times since March 2021. 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.
For an individual, I used to use WikidPad and quite like it. Source: about 1 year ago
There also are "serverless" wikis, like http://tiddlywiki.com/ (can be run as a standalone desktop app - see in the bottom, or Wiki on a Stick, or WikiPad. Source: about 1 year ago
Wikidpad is quite functional. It's not the prettiest but it does its job. I don't know if or how you can implement images. But it's free and maybe worth a try. Source: over 1 year ago
Is it this one? http://wikidpad.sourceforge.net/ Also is it on mobile, and does it support images? Source: almost 2 years ago
If your work is not published its very likely to be removed by a mod on Wikipedia, but when it comes to organizing your world, a personal wiki is by far the best way to do so. There are lots of tools out there, both free and premium. I would recommend doing some research on all of the suggestions in this thread and find what works for you. Wikidpad is a free desktop wiki that's super handy when you just want to... Source: almost 2 years ago
AWS Rekognition is a great choice for many types of real-world projects or just for testing an idea on your images. The issue eventually comes with its cost, unfortunately, which we will see later in a specific example. Don’t get me wrong, Rekognition is a great service and I love to use it for its simplicity and reliable performance on quite a few projects. - Source: dev.to / 2 months ago
I don’t really want to spend so much time manually adjusting labels. For most machine learning, the next step would be to fine tune your model. You can essentially fine tune Amazon Rekognition by using Custom Labels. You can do this to make it better at detecting specific objects (like bears) or train it to detect new objects like your product or logo. It really depends on your application needs. - Source: dev.to / 11 months ago
For instance, are you a company with lots of security cameras? Hire me to write a program that pipes your data into AWS rekognition and then shows you a dashboard of what happened on your cams today. Got a ton of products with no meta-description? Hire me to write a program that pipes your data into OpenAI, and then saves the generated description to your custom CMS. Source: 11 months ago
Amazon Rekognition: Used to index, detect faces in the picture, and compare faces when users try voting, it was the heart of the facial voting feature. - Source: dev.to / about 1 year ago
Sure. But if you think generating thumbnails and detecting intros/credits takes a long time, wait until your computer is running machine learning/computer vision over your entire library. They also have to build and train that model which is no trivial task. And I know what you're thinking, why don't they just use Amazon's Rekognition service that does celebrity identification? Well, it's $0.10 per minute of... Source: about 1 year ago
OneNote - Get the OneNote app for free on your tablet, phone, and computer, so you can capture your ideas and to-do lists in one place wherever you are. Or try OneNote with Office for free.
Google Vision AI - Cloud Vision API provides a comprehensive set of capabilities including object detection, ocr, explicit content, face, logo, and landmark detection.
Evernote - Bring your life's work together in one digital workspace. Evernote is the place to collect inspirational ideas, write meaningful words, and move your important projects forward.
Clarifai - The World's AI
Zim Wiki - Zim is a graphical text editor used to maintain a collection of wiki pages. Each page can contain links to other pages, simple formatting and images.
Kairos - Facial recognition & mood detection API