Check out the latest State-of-the-Art YOLO Model for Object Detection
Hello trend,
This is Satya Mallick from LearnOpenCV.com.
The much awaited YOLO version - YOLOv8 from Ultralytics has been released.
Ultralytics have released a completely new repository and a very user-friendly API (Command line as well as Python). It is built as a unified framework for training Object Detection and Instance Segmentation.(🤫 it also supports Image Classification).
Here are some key features about the new release:
- Easy to use API (Command Line + Python).
- Faster and More Accurate.
- Supports
- Object Detection,
- Instance Segmentation,
- Image Classification.
- Extensible to all previous versions.
- New Backbone network.
- New Anchor-Free head.
- New Loss Function.
Without further ado, let's jump into the details of YOLOv8:
Ultralytics YOLOv8 Object Detection SoTA |
In case you missed it, here's the complete list of posts from the YOLO series:
- YOLOR Paper Explanation and Comparison
- YOLOv6 Custom Training for Underwater Trash Detection
- YOLOv6 Object Detector Paper Explanation and Inference
- YOLOX Object Detector and Custom Training on Drone Dataset
- YOLOv7 Object Detector Training on Custom Dataset
- YOLOv7 Object Detector Paper Explanation and Inference
- YOLOv5 Custom Object Detector Training on Vehicles Dataset
- YOLOv5 Object Detection using OpenCV DNN
- YOLOv4 - Training a Custom Pothole Detector
Is there any other YOLO model that you want us to research upon?
Cheers!
Satya
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