Product
Solutions
Resources
Pricing
Docs
Talk to SalesSign in
Models
YOLOv3 PyTorch vs. Scaled-YOLOv4

Explore Models

By Task
All Models (32)Object Detection Models (19)Classification Models (7)Instance Segmentation Models (3)Semantic Segmentation Models (1)
By Feature
Foundation Vision ModelsMultimodal Vision ModelsImage Embedding ModelsReal Time Vision ModelsZero-Shot Detection ModelsOptimal for Edge Deployment

YOLOv3 PyTorch vs. Scaled-YOLOv4

Both

YOLOv3 PyTorch

and

Scaled YOLOv4

are commonly used in computer vision projects. Below, we compare and contrast

YOLOv3 PyTorch

and

Scaled YOLOv4

.

  YOLOv3 PyTorch Scaled YOLOv4
Date of Release Apr 08, 2018
Model Type Object Detection Object Detection
Architecture YOLO
GitHub Stars 6800 2000

YOLOv3 PyTorch

Though it is no longer the most accurate object detection algorithm, YOLO v3 is still a very good choice when you need real-time detection while maintaining excellent accuracy. PyTorch version.

How to AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion Matrix

Scaled YOLOv4

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

How to AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion Matrix
Learn more about YOLOv3 PyTorch
Learn more about Scaled YOLOv4

Compare YOLOv3 PyTorch to other models

MobileNet V2 Classification
MobileNet SSD v2
YOLOv4 PyTorch
YOLOv4 Darknet
YOLOv4 Tiny

Compare Scaled YOLOv4 to other models

YOLOv8 Instance Segmentation
YOLOv8
YOLOv7 Instance Segmentation
OneFormer
MobileNet V2 Classification

Deploy a computer vision model today

Join 250,000 developers curating high quality datasets and deploying better models with Roboflow.

Get started