YOLOv7 Instance Segmentation vs. YOLOR

Both YOLOv7 Instance Segmentation and YOLOR are commonly used in computer vision projects. Below, we compare and contrast YOLOv7 Instance Segmentation and YOLOR.

Models

YOLOv7 Instance Segmentation

YOLOv7 Instance Segmentation lets you perform segmentation tasks with the YOLOv7 model.

Learn more about YOLOv7 Instance Segmentation

YOLOR

YOLOR (You Only Learn One Representation) is an object detection model that uses both implicit and explicit knowledge to make predictions.

Learn more about YOLOR

Model Type

Instance Segmentation

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

YOLO

CNN, YOLO

Frameworks

PyTorch

Annotation Format

Instance Segmentation

GitHub

View Repo

GitHub Stars

12.5k+

2k+

License

GPL-3.0

Paper

View Paper

Training Notebook

Train on Colab

Deploy Model

Deploy with Roboflow

Compare YOLOv7 Instance Segmentation vs. YOLOR

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.

YOLOv7 Instance Segmentation vs. YOLOR

Models