Models
MT-YOLOv6 vs. YOLOv4 PyTorch

MT-YOLOv6 vs. YOLOv4 PyTorch

Both MT-YOLOv6 and YOLOv4 PyTorch are commonly used in computer vision projects. Below, we compare and contrast MT-YOLOv6 and YOLOv4 PyTorch.

Models

icon-model

MT-YOLOv6

MT-YOLOv6 is a YOLO based model released in 2022.
Learn more about MT-YOLOv6
icon-model

YOLOv4 PyTorch

YOLOv4 has emerged as the best real time object detection model. YOLOv4 carries forward many of the research contributions of the YOLO family of models along with new modeling and data augmentation techniques. This implementation is in PyTorch.
Learn more about YOLOv4 PyTorch
Model Type
Object Detection
--
Object Detection
--
Model Features
Item 1 Info
Item 2 Info
Architecture
CNN, YOLO
--
YOLO
--
Frameworks
PyTorch
--
PyTorch
--
Annotation Format
Instance Segmentation
Instance Segmentation
GitHub
--
View Repo
--
View Repo
GitHub Stars
5.5k+
--
4.4k+
--
License
GPL-3.0
--
Apache-2.0
--
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 MT-YOLOv6 and YOLOv4 PyTorch with Autodistill

Compare MT-YOLOv6 vs. YOLOv4 PyTorch

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.