darknet
darknet_ros
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| darknet | darknet_ros | |
|---|---|---|
| 62 | 4 | |
| 21,434 | 2,076 | |
| - | 2.8% | |
| 7.0 | 0.0 | |
| about 1 month ago | 8 months ago | |
| C | C++ | |
| GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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.
darknet
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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.
darknet_ros
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Resources for obstacle avoidance
Sorry got swamped with exams, here is the darknet-ros repo: https://github.com/leggedrobotics/darknet_ros
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Yolo in ROS
You are using „darknet_ros“ package. That information probably belongs in the post. I do not have experience with that package. You should look into your logfile and try debug why it is shutting down. If you have further problems with the package. You should try to open a issue on GitHub. https://github.com/leggedrobotics/darknet_ros
Look at Issue here
- How can I Integrate YOLO algorithm in ROS for Lane and Vehicle Detection ?
What are some alternatives?
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
jetson-inference - Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
tensorflow-yolov4-tflite - YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
yolo-tf2 - yolo(all versions) implementation in keras and tensorflow 2.x
tensorflow-yolo-v3 - Implementation of YOLO v3 object detector in Tensorflow (TF-Slim)
carla - Open-source simulator for autonomous driving research.
efficientdet-pytorch - A PyTorch impl of EfficientDet faithful to the original Google impl w/ ported weights
DarkHelp - C++ wrapper library for Darknet
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
DarkPlate - License plate parsing using Darknet and YOLO
tensorflow-lite-YOLOv3 - YOLOv3: convert .weights to .tflite format for tensorflow lite. Convert .weights to .pb format for tensorflow serving
PreciseRoIPooling - Precise RoI Pooling with coordinate gradient support, proposed in the paper "Acquisition of Localization Confidence for Accurate Object Detection" (https://arxiv.org/abs/1807.11590).