Highlight interesting links. Hide irrelevant ones. Remove whole websites from search results. Cyberpunk! Updated bookmark experience We all know what “bookmark” in every browser does, don’t we? What if I told you that bookmarks were insufficient and could be improved? I’m here to show you how :)
We usually add something valuable there, stuff we want to read later when we have time or not feeling lazy. It’s pretty usual for most of us that the “read later” folder is becoming “probably read later” and then finally “don’t know what’s here”.
How do we change it? Add the reminder to the link: set it up for the day you’re going to have some spare time, add a Mark to remind why you should do it. That’s the spirit!
What about valueless stuff? Links we don’t want to open again. “Why would we want it?” - you’re going to ask. Fair question. Have you ever been looking for an apartment? You should know then how it is to open the same apartment every day forgetting that you rejected it (and why). Once again you open the photo of the bathroom: “Ah, yeah, this bath is ugly...”. Don’t worry, you’re going to open the same room again tomorrow, the title photo is so promising…
Not with MarkALink! Add the link to the “Hide” group and forget about coming to this useless page henceforth. Whenever and wherever you see this link on the web, you’ll recognize it. And it’s only one of the cases where it could optimize your processes and save your time!
Based on our record, Computer Vision Annotation Tool (CVAT) seems to be more popular. It has been mentiond 14 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.
Another powerful resource is CVAT, the Computer Vision Annotation Tool which supports both image and video annotations with advanced capabilities such as interpolation of shapes between frames, making it highly suitable for computer vision. - Source: dev.to / 5 months ago
CVAT has an open source repo under MIT license: https://github.com/opencv/cvat I've not worked with it directly but it might be a good place to start. Source: 5 months ago
An open source annotation tool that integrates object detectors is CVAT https://github.com/opencv/cvat however, using your own detector might require some coding. There is an integration for yolov5, but without modification it only loads the pretrained models. Source: 12 months ago
This integration is currently available in the open-source version of Computer Vision Annotation Tool (http://github.com/opencv/cvat)! Please use it for your computer vision projects to segment images faster. - Source: Hacker News / about 1 year ago
You can download the CVAT docker from a github (Link) and install it yourself, keeping all data local. And here are two options - locally on your personal computer (or company server) or in your own cloud (there are instructions on how to do this with AWS). - Source: dev.to / about 1 year ago
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