YOLOv6
yolov7_d2
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YOLOv6 | yolov7_d2 | |
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11 | 4 | |
5,530 | 3,130 | |
1.3% | - | |
6.7 | 0.0 | |
about 2 months ago | 5 months ago | |
Jupyter Notebook | Python | |
GNU General Public License v3.0 only | GNU General Public License v3.0 only |
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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
yolov7_d2
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YOLOv7: Trainable Bag-of-Freebies
Especially hilarious considering some other people ALSO jumped on the "we made an object detector so let's call it YOLOvX" wagon and released...
Something called YOLOv7.
https://github.com/jinfagang/yolov7
- YOLOv7: YOLO with Transformers and Instance Segmentation
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How to Train YOLOv6 on a Custom Dataset
You're 9 months late https://github.com/jinfagang/yolov7
- YOLOv6: Redefine state-of-the-art for object detection
What are some alternatives?
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
edgetpu-yolo - Minimal-dependency Yolov5 export and inference demonstration for the Google Coral EdgeTPU
edgetpu - Coral issue tracker (and legacy Edge TPU API source)
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/
YOLOv4 - Port of YOLOv4 to C# + TensorFlow
keras-yolo3 - Training and Detecting Objects with YOLO3
BCNet - Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [CVPR 2021]
PixelLib - Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/
yolact - A simple, fully convolutional model for real-time instance segmentation.