DarkMark
Marking up images for use with Darknet. (by stephanecharette)
DarkPlate
License plate parsing using Darknet and YOLO (by stephanecharette)
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| DarkMark | DarkPlate | |
|---|---|---|
| 8 | 6 | |
| 144 | 53 | |
| - | - | |
| 6.9 | 0.0 | |
| about 2 months ago | about 1 year ago | |
| C++ | C++ | |
| GNU General Public License v3.0 or later | MIT License |
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.
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
DarkPlate
Posts with mentions or reviews of DarkPlate.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-09-26.
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Need Help to Design an OCR for number plate test extraction
Take a look at DarkPlate, which can process either videos or static images: https://github.com/stephanecharette/DarkPlate
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Help with video data for custom yolov3 model
This is how I would do it: https://github.com/stephanecharette/DarkPlate
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I have a set of images with instances of two classes are labeled on it. Can I train Yolo V5 or V4 to detect both classes on a test image?
Here is an example project with 37 classes, and all the images are within the same folder: https://github.com/stephanecharette/DarkPlate/tree/master/nn
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What is the best way to process video frames in darknet for YOLO object detection?
1) At the very bottom of this page: https://www.ccoderun.ca/darkhelp/api/API.html 2) This example github project: https://github.com/stephanecharette/DarkPlate
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What are some of the best models/approaches for number plate recognition?
I use YOLOv4-tiny. I make two passes with the same neural network. First pass to find the plate, 2nd pass to read the characters. Demo (skip to 86 seconds): https://www.youtube.com/watch?v=jz97_-PCxl4&t=86s and code: https://github.com/stephanecharette/DarkPlate
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need advice on a opencv project [Question] [Project]
See here for example, where frames are extracted and then passed to the neural network for processing: https://github.com/stephanecharette/DarkPlate/blob/master/src/main.cpp#L216-L217
What are some alternatives?
When comparing DarkMark and DarkPlate you can also consider the following projects:
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
DarkHelp - C++ wrapper library for Darknet
image-quality-assessment - Convolutional Neural Networks to predict the aesthetic and technical quality of images.
darknet - YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
django-labeller - An image labelling tool for creating segmentation data sets, for Django and Flask.
deep-license-plate-recognition - Automatic License Plate Recognition (ALPR) or Automatic Number Plate Recognition (ANPR) software that works with any camera.
VIAME - Video and Image Analytics for Multiple Environments
Pine - :evergreen_tree: Aimbot powered by real-time object detection with neural networks, GPU accelerated with Nvidia. Optimized for use with CS:GO.
anpr - Issue tracker e documentazione di ANPR - Anagrafe Nazionale della Popolazione Residente
openpose - OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
darknet_ros - YOLO ROS: Real-Time Object Detection for ROS