![]() ![]() ( by Comet Logging and Visualization Integration: Free forever, Comet lets you save YOLOv5 models, resume training, and interactively visualise and debug predictions. This reduces risk in caching and should help improve adoption of the dataset caching feature, which can significantly speed up training. Important Updates Segmentation Models ⭐ NEW: SOTA YOLOv5-seg COCO-pretrained segmentation models are now available for the first time ( by and Paddle Paddle Export: Export any YOLOv5 model (cls, seg, det) to Paddle format with python export.py -include paddle ( by YOLOv5 AutoCache: Use python train.py -cache ram will now scan available memory and compare against predicted dataset RAM usage. We'd love your feedback and contributions on this effort! This release incorporates 280 PRs from 41 contributors since our last release in August 2022. The new v7.0 YOLOv5-seg models below are just a start, we will continue to improve these going forward together with our existing detection and classification models. ![]() ![]() Our primary goal with this release is to introduce super simple YOLOv5 segmentation workflows just like our existing object detection models. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |