Models
YOLOv4 vs. Faster R-CNN

YOLOv4 vs. Faster R-CNN

Both YOLOv4 Darknet and Faster R-CNN are commonly used in computer vision projects. Below, we compare and contrast YOLOv4 Darknet and Faster R-CNN.

Models

icon-model

YOLOv4 Darknet

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 Darknet.
icon-model

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.
Model Type
Object Detection
--
Object Detection
--
Model Features
Item 1 Info
Item 2 Info
Architecture
YOLO
--
--
Frameworks
Darknet
--
TensorFlow 1.5
--
Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
--
7.5k+
--
License
YOLO
--
MIT
--
Training Notebook

Compare YOLOv4 Darknet and Faster R-CNN with Autodistill

Compare YOLOv4 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.