NerOne
Low level C++ neural network engine. The engine provides a huge flexibility in creating neural networks. It also gives an ability for performance optimisations. (by Immortale-dev)
DarkMark
Marking up images for use with Darknet. (by stephanecharette)
| NerOne | DarkMark | |
|---|---|---|
| 1 | 8 | |
| 9 | 146 | |
| - | - | |
| 7.6 | 6.9 | |
| 4 months ago | about 2 months ago | |
| C++ | C++ | |
| MIT License | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
NerOne
Posts with mentions or reviews of NerOne.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-19.
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C++ neural network low level engine
Hello everybody! I want to share one thing I worked on for the last 2 months. https://github.com/Immortale-dev/NerOne
DarkMark
Posts with mentions or reviews of DarkMark.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-06-13.
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Using YOLO for annotation in CVAT
Also see DarkMark. For several years it has had support for loading custom Darknet/YOLO weights (not just MSCOCO!) to help annotate more images. https://www.ccoderun.ca/darkmark/Summary.html
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[Discussion] YOLOv5 training questions, specificaly re-training best practices
You should look at DarkMark. I wrote it specifically to do what you describe. It is an annotation tool that loads the Darknet/YOLO weights, so it can assist in annotating images. I annotate a few images and train, reload DarkMark to annotate some more, train, rinse, lather, repeat.
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When to use YOLOv5 and when not to use the model?
Disclaimer: I'm the author of DarkHelp (the C++ library for Darknet) and DarkMark (the annotation and project management tool for Darknet).
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Annotate data for tracking
If using Darknet/YOLO, look up DarkMark which does have support for video, as well as loading existing neural networks to help annotate images (or video frames) faster. Some info on getting started: https://www.ccoderun.ca/programming/darknet\_faq/#how\_to\_get\_started
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Free AI assisted image labelling tool
You can find DarkMark here: https://github.com/stephanecharette/DarkMark
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Reduce false positive in object detection
Disclaimer: I'm the author of DarkHelp and DarkMark, and I run the Darknet/YOLO discord.
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Extracting Images from Video
I use DarkMark's video import functionality to extract video frames. See this screenshot: https://www.ccoderun.ca/darkmark/Summary.html#DarkMarkImportVideoFrames
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Annotating and detecting objects in a video
DarkMark will extract frames from a video (lots of options, either all frames, sequences of frames, random number of frames, png vs jpeg, resize frames, ...) and then will let you annotate them as you normally would. https://github.com/stephanecharette/DarkMark
What are some alternatives?
When comparing NerOne and DarkMark you can also consider the following projects:
Seayon - Open source Neural Network library in C++
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite