Models
YOLOv4 Tiny vs. Scaled-YOLOv4

YOLOv4 Tiny vs. Scaled-YOLOv4

Both YOLOv4 Tiny and Scaled YOLOv4 are commonly used in computer vision projects. Below, we compare and contrast YOLOv4 Tiny and Scaled YOLOv4.

Models

icon-model

YOLOv4 Tiny

The tiny and fast version of YOLOv4 - good for training and deployment on limited compute resources, and getting a feel for your dataset
Learn more about YOLOv4 Tiny
icon-model

Scaled YOLOv4

Scaled YOLOv4 is an extension of the YOLOv4 research implemented in the YOLOv5 PyTorch framework.
Learn more about Scaled YOLOv4
Model Type
Object Detection
--
Object Detection
--
Model Features
Item 1 Info
Item 2 Info
Architecture
ResNet-D, YOLO
--
YOLO
--
Frameworks
Darknet
--
PyTorch
--
Annotation Format
Instance Segmentation
Instance Segmentation
GitHub
--
View Repo
--
View Repo
GitHub Stars
--
2k+
--
License
YOLO
--
GPL-3.0
--
Paper
--
View Paper
--
View Paper
Training Notebook
Train on Colab
--
Train on Colab
--
Deploy Model
--
rocket icon
Deploy with Roboflow
--
rocket icon
Deploy with Roboflow
Compare Alternatives
--
Compare with...
--
Compare with...

Compare YOLOv4 Tiny and Scaled YOLOv4 with Autodistill

Compare YOLOv4 Tiny vs. Scaled-YOLOv4

Provide your own image below to test YOLOv8 and YOLOv9 model checkpoints trained on the Microsoft COCO dataset.

COCO can detect 80 common objects, including cats, cell phones, and cars.