yolact
YOLOv6
| yolact | YOLOv6 | |
|---|---|---|
| 4 | 11 | |
| 4,931 | 5,549 | |
| - | 0.9% | |
| 0.0 | 6.7 | |
| 6 months ago | about 2 months ago | |
| Python | Jupyter Notebook | |
| MIT License | GNU General Public License v3.0 only |
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yolact
- YOLOv6: Redefine state-of-the-art for object detection
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Instance segmentation
YOLACT
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Advice needed
The Github repo is not highly structured and is probably written during the time of the author's research. Been using this for well over a year and does the job so well.
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A question on Instance Segmentation Labelling
I am using yolact : https://github.com/dbolya/yolact
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?
Mask_RCNN - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
yolact_edge - The first competitive instance segmentation approach that runs on small edge devices at real-time speeds.
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
yolov3-tf2 - YoloV3 Implemented in Tensorflow 2.0
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
mmdetection - OpenMMLab Detection Toolbox and Benchmark
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/
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
keras-yolo3 - Training and Detecting Objects with YOLO3
yolo_tracking - BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models
PixelLib - Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/