yolo_series_deepsort_pytorch
YOLOv6
| yolo_series_deepsort_pytorch | YOLOv6 | |
|---|---|---|
| 1 | 11 | |
| 93 | 5,541 | |
| - | 0.8% | |
| 0.0 | 6.7 | |
| about 1 year ago | about 2 months ago | |
| Python | Jupyter Notebook | |
| MIT License | GNU General Public License v3.0 only |
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yolo_series_deepsort_pytorch
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DeepSort with PyTorch(support yolo series)
git clone https://github.com/xuarehere/yolovx_deepsort_pytorch.git
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?
deep_sort - Simple Online Realtime Tracking with a Deep Association Metric
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
PPYOLOE_pytorch - An unofficial implementation of Pytorch version PP-YOLOE,based on Megvii YOLOX training code.
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
hcaptcha-challenger - 🥂 Gracefully face hCaptcha challenge with MoE(ONNX) embedded solution.
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
segment-anything-video - MetaSeg: Packaged version of the Segment Anything repository
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/
ScaledYOLOv4 - Scaled-YOLOv4: Scaling Cross Stage Partial Network
keras-yolo3 - Training and Detecting Objects with YOLO3
deep_sort_realtime - A really more real-time adaptation of deep sort
PixelLib - Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/