keras-yolo3
YOLOv6
| keras-yolo3 | YOLOv6 | |
|---|---|---|
| 1 | 11 | |
| 1,606 | 5,541 | |
| - | 0.8% | |
| 0.0 | 6.7 | |
| 8 months ago | about 2 months ago | |
| Python | Jupyter Notebook | |
| MIT License | GNU General Public License v3.0 only |
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keras-yolo3
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What’s Destroying My Yard? Pest Detection with Raspberry Pi
I've always been facinated by the usage of the Pi. I think of the methods used when you have a pi, versus not having one. It looks like a fun project if you have all the parts, but I don't so I thought of this alternative!
A method I thought of was just a camera that will utilize yolo3 https://github.com/experiencor/keras-yolo3 or just an always on security camera that you can just skip through the video to see all the activity with less setup, and seeing what animals cause issues. The jetson for faster 'edgey' visual ML models might be an option for those who want a stronger NPU, but using online GPU/NPU tokens and GPUs on computers if you don't need live feedback is very effective.
YOLOv6
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I want to make a Class monitoring system. is it possible in the conditions I'm in ??
Some resources to get you started...https://towardsdatascience.com/object-detection-with-10-lines-of-code-d6cb4d86f606https://github.com/OlafenwaMoses/ImageAIhttps://towardsdatascience.com/yolo-object-detection-with-opencv-and-python-21e50ac599e9https://github.com/meituan/YOLOv6
- [P] Any object detection library
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DeepSort with PyTorch(support yolo series)
meituan/YOLOv6
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Tried to install requirements.txt with pip for YOLOv6.
Have you looked at this open github issue? It might be that you do not need to/should not install it using pip.
- A single-stage object detection framework dedicated to industrial applications
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YOLOv6: Redefine state-of-the-art for object detection
https://github.com/meituan/YOLOv6/blob/main/docs/About_namin...
> P.S. We are contacting the authors of YOLO series about the naming of YOLOv6.
You should ask _before_ publishing, not _after_.
They claim it runs faster and is more accurate than YOLOv5, yet requires 3x as much computation (GFLOPs)? Something doesn't add up here.
There is unbelievably little information about the architecture too. Unfortunately it's not in a format I can easily throw the cfg in as visualize it: https://gitlab.com/danbarry16/darknet-visual
This appears to be on purpose to advertise DagsHub: https://dagshub.com/pricing
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[D][P] YOLOv6: state-of-the-art object detection at 1242 FPS
Saved you the time: https://github.com/meituan/YOLOv6
- Is YOLOv6 actually a significant improvement over YOLOv5?
- YOLOv6 is out
What are some alternatives?
tensorflow-yolo-v3 - Implementation of YOLO v3 object detector in Tensorflow (TF-Slim)
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
YOLOX - YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
ultralytics - NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
PixelLib - Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/
edgetpu-yolo - Minimal-dependency Yolov5 export and inference demonstration for the Google Coral EdgeTPU
edgetpu - Coral issue tracker (and legacy Edge TPU API source)