DarkPlate
License plate parsing using Darknet and YOLO (by stephanecharette)
darknet
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet ) (by AlexeyAB)
DarkPlate | darknet | |
---|---|---|
6 | 62 | |
53 | 21,466 | |
- | - | |
0.0 | 6.5 | |
about 1 year ago | 1 day 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.
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
darknet
Posts with mentions or reviews of darknet.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-21.
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Anybody building ML models in C++?
YoloV3/4 is C based if that counts: https://github.com/AlexeyAB/darknet
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[D] Fixing the angle of Skewed Paintings, see comments
This is all well-known information, see any (and all!) previous discussions when YOLOv5 comes up. For details: https://github.com/AlexeyAB/darknet/issues/5920
- Viseron 2.0.0 - Self-hosted, local only NVR and AI Computer Vision software.
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How do I train YOLO5 to detect small objects (arial imagery). something like 20-20 pixels or maybe little more? How do I increase resolution and apply augmentation and tiling? Or maybe the YOLO5 is not he best choice for that?
2) YOLOv5 is both slower and less precise than YOLOv4. Why use YOLOv5? Source: https://github.com/AlexeyAB/darknet/issues/5920
- Machine learning Library in C?
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I just realized yolov5 is GPL-3
So my recommendation is you stuck with Darknet/YOLO and use v4 of YOLO. The Darknet framework license is definitely suitable for commercial use: https://github.com/AlexeyAB/darknet/blob/master/LICENSE
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GPL vs MIT.
Still to long. Here's my favourite license: https://github.com/AlexeyAB/darknet/blob/master/LICENSE
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I was excited about YOLOv7, so I built a sharable object detection application with VDP and Streamlit.
When YOLOv7 was out, I built a web app to test it against the classic YOLOv4 and shared it with my team, then deployed it online to share with the community.
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Does reducing the number of classes on YOLOv5 make it faster at inference?
If you're worried about performance, you shouldn't be using YOLOv5 since it is slower (and less accurate!) than YOLOv4. Source: https://github.com/AlexeyAB/darknet/issues/5920
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[D] DarkNet YOLOv4 with CUDA 11.7 in Windows?
I looked around online but I only found this post discussing a related issue, leading me to think there seems to be some sort of compatibility issue going on here. And I think this is the most recent version of the file I am trying to compile located on the exact same folder where my copy is and when I opened it it shows CUDA 11.1 in line 307.