MT-YOLOv6 vs. Faster R-CNN

Both MT-YOLOv6 and Faster R-CNN are commonly used in computer vision projects. Below, we compare and contrast MT-YOLOv6 and Faster R-CNN.

Models

MT-YOLOv6

MT-YOLOv6 is a YOLO based model released in 2022.

Learn more about MT-YOLOv6

Faster R-CNN

One of the most accurate object detection algorithms but requires a lot of power at inference time. A good choice if you can do processing asynchronously on a server.

Learn more about Faster R-CNN

Model Type

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

CNN, YOLO

Annotation Format

Instance Segmentation

Framework

PyTorch

TensorFlow 1.5

GitHub

View Repo

GitHub Stars

5.5k+

7.5k+

License

GPL-3.0

MIT

Paper

View Paper

Training Notebook

Train on Colab

Deploy Model

Deploy with Roboflow

Compare MT-YOLOv6 vs. Faster R-CNN

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.

MT-YOLOv6 vs. Faster R-CNN

Models

MT-YOLOv6

Faster R-CNN

Compare MT-YOLOv6 and Faster R-CNN with Autodistill

Compare MT-YOLOv6 vs. Faster R-CNN