Resnet-32 vs. YOLOv3 PyTorch

Both ResNet 32 and YOLOv3 PyTorch are commonly used in computer vision projects. Below, we compare and contrast ResNet 32 and YOLOv3 PyTorch.

Models

ResNet 32

A fast, simple convolutional neural network that gets the job done for many tasks, including classification.

Learn more about ResNet 32

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.

Learn more about YOLOv3 PyTorch

Model Type

Classification

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

YOLO

Frameworks

Fast.ai v2

PyTorch

Annotation Format

Instance Segmentation

GitHub

View Repo

GitHub Stars

32+

7.2k+

License

GPL-3.0

Paper

View Paper

Training Notebook

Train on Colab

Deploy Model

Deploy with Roboflow

Compare Resnet-32 vs. YOLOv3 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.

Resnet-32 vs. YOLOv3 PyTorch

Models

ResNet 32

YOLOv3 PyTorch

Compare ResNet 32 and YOLOv3 PyTorch with Autodistill

Compare Resnet-32 vs. YOLOv3 PyTorch