From f955fedb7f7dbf92bd062a89577d692eea53e9ce Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Tue, 30 Jul 2024 03:51:48 +0200 Subject: [PATCH] SAM2 mkdocs.yml fix (#14796) --- docs/en/models/sam2.md | 4 ++-- mkdocs.yml | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/en/models/sam2.md b/docs/en/models/sam2.md index 34a384be..5c586d4c 100644 --- a/docs/en/models/sam2.md +++ b/docs/en/models/sam2.md @@ -4,12 +4,12 @@ description: Discover SAM2, the next generation of Meta's Segment Anything Model keywords: SAM2, Segment Anything, video segmentation, image segmentation, promptable segmentation, zero-shot performance, SA-V dataset, Ultralytics, real-time segmentation, AI, machine learning --- +# SAM2: Segment Anything Model 2 + !!! Note "🚧 SAM2 Integration In Progress 🚧" The SAM2 features described in this documentation are currently not enabled in the `ultralytics` package. The Ultralytics team is actively working on integrating SAM2, and these capabilities should be available soon. We appreciate your patience as we work to implement this exciting new model. -# SAM2: Segment Anything Model 2 - SAM2, the successor to Meta's [Segment Anything Model (SAM)](sam.md), is a cutting-edge tool designed for comprehensive object segmentation in both images and videos. It excels in handling complex visual data through a unified, promptable model architecture that supports real-time processing and zero-shot generalization. ![SAM2 Example Results](https://github.com/facebookresearch/segment-anything-2/raw/main/assets/sa_v_dataset.jpg?raw=true) diff --git a/mkdocs.yml b/mkdocs.yml index 6fd25098..c991f848 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -239,7 +239,7 @@ nav: - YOLOv9: models/yolov9.md - YOLOv10: models/yolov10.md - SAM (Segment Anything Model): models/sam.md - - SAM2 (Segment Anything Model 2): models/sam.md + - SAM2 (Segment Anything Model 2): models/sam2.md - MobileSAM (Mobile Segment Anything Model): models/mobile-sam.md - FastSAM (Fast Segment Anything Model): models/fast-sam.md - YOLO-NAS (Neural Architecture Search): models/yolo-nas.md