Faster R-CNN vs. YOLOv4 PyTorch: Compared and Contrasted

Models

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

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

Model Features

Item 1 Info

Item 2 Info

Architecture

YOLO

Frameworks

TensorFlow 1.5

PyTorch

Annotation Format

Instance Segmentation

GitHub

View Repo

GitHub Stars

7.5k+

4.4k+

License

MIT

Apache-2.0

Paper

Training Notebook

Deploy Model

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Faster R-CNN vs. YOLOv4 PyTorch

Both

Faster R-CNN

and

YOLOv4 PyTorch

are commonly used in computer vision projects. Below, we compare and contrast

Faster R-CNN

and

YOLOv4 PyTorch

	Faster R-CNN	YOLOv4 PyTorch
Date of Release
Model Type	Object Detection	Object Detection
Architecture		YOLO
GitHub Stars	7500	4400

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.

How to Augment How to Label How to Plot Predictions How to Filter Predictions How to Create a Confusion Matrix