mmyolo/configs/yolov5/README.md

YOLOv5

Abstract

YOLOv5 is a family of object detection architectures and models pretrained on the COCO dataset, and represents Ultralytics open-source research into future vision AI methods, incorporating lessons learned and best practices evolved over thousands of hours of research and development.

Results and models

COCO

Backbone	size	SyncBN	AMP	Mem (GB)	box AP	Config	Download
YOLOv5-n	640	Yes	Yes	xxx	xxx	config	model | log
YOLOv5-s	640	Yes	Yes	xxx	xxx	config	model | log
YOLOv5-m	640	Yes	Yes	xxx	xxx	config	model | log
YOLOv5-l	640	Yes	Yes	xxx	xxx	config	model | log
YOLOv5-x	640	Yes	Yes	xxx	xxx	config	model | log

Note:

1. fast means that YOLOv5DetDataPreprocessor and yolov5_collate are used for data preprocessing, which is faster for training, but less flexible for multitasking. Recommended to use fast version config if you only care about object detection.
2. SyncBN means use SyncBN, AMP indicates training with mixed precision.
3. We use 8x A100 for training, and the single-GPU batch size is 16. This is different from the official code.
4. The performance is unstable and may fluctuate by about 0.4 mAP. mAP 37.3 ~ 37.7 is acceptable in YOLOv5-s.