Models

What is Scaled YOLOv4?

Scaled YOLOv4 is an extension of the YOLOv4 research implemented in the YOLOv5 PyTorch framework.

About the model

Here is an overview of the

Scaled YOLOv4

model:

Date of Release
Model Type Object Detection
Architecture
Framework Used PyTorch
Annotation Format Scaled-YOLOv4 TXT
Stars on GitHub 2000+

What is Scaled YOLOv4

Scaled YOLOv4 is an extension of the YOLOv4 research, developed by Chien-Yao Wang, Alexey Bochkovskiy, and Hong-Yuan Mark Liao, and implemented in the YOLOv5 PyTorch framework. At its core, it primarily lies on Cross Stage Partial Networks, allowing the network to scale its depth, width, resolution, and structure while maintaining speed and accuracy.

Scaled YoloV4 Results

Scaled Yolov4 Results

Learn More

More info here: https://blog.roboflow.com/scaled-yolov4-tops-efficientdet/

Check out YOLOv8, defining a new state-of-the-art in computer vision

YOLOv8 is here, setting a new standard for performance in object detection and image segmentation tasks. Roboflow has developed a library of resources to help you get started with YOLOv8, covering guides on how to train YOLOv8, how the model stacks up against v5 and v7, and more.

Learn about YOLOv8

Check out YOLOv8, defining a new state-of-the-art in computer vision

YOLOv8 is here, setting a new standard for performance in object detection and image segmentation tasks. Roboflow has developed a library of resources to help you get started with YOLOv8, covering guides on how to train YOLOv8, how the model stacks up against v5 and v7, and more.

Learn about YOLOv8

Check out YOLOv8, defining a new state-of-the-art in computer vision

YOLOv8 is here, setting a new standard for performance in object detection and image segmentation tasks. Roboflow has developed a library of resources to help you get started with YOLOv8, covering guides on how to train YOLOv8, how the model stacks up against v5 and v7, and more.

Learn about YOLOv8

Check out YOLOv8, defining a new state-of-the-art in computer vision

YOLOv8 is here, setting a new standard for performance in object detection and image segmentation tasks. Roboflow has developed a library of resources to help you get started with YOLOv8, covering guides on how to train YOLOv8, how the model stacks up against v5 and v7, and more.

Learn about YOLOv8

Model Performance

Explore this model on Roboflow

Deploy Scaled YOLOv4 to production

Roboflow offers a range of SDKs with which you can deploy your model to production.

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Scaled YOLOv4 Annotation Format

Scaled YOLOv4

uses the

uses the

Scaled-YOLOv4 TXT

annotation format. If your annotation is in a different format, you can use Roboflow's annotation conversion tools to get your data into the right format.

Convert data between formats

Label data automatically with Scaled YOLOv4

You can automatically label a dataset using

Scaled YOLOv4

with help from Autodistill, an open source package for training computer vision models. You can label a folder of images automatically with only a few lines of code. Below, see our tutorials that demonstrate how to use

Scaled YOLOv4

to train a computer vision model.

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