From dacbd48fcf8407098166c6812eeb751deaac0faf Mon Sep 17 00:00:00 2001 From: Muhammad Rizwan Munawar Date: Sat, 22 Jun 2024 00:07:39 +0500 Subject: [PATCH] Add https://youtu.be/tq3FU_QczxE to docs (#13867) Co-authored-by: Glenn Jocher --- docs/en/guides/sahi-tiled-inference.md | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/docs/en/guides/sahi-tiled-inference.md b/docs/en/guides/sahi-tiled-inference.md index e9287b3c..7d82087c 100644 --- a/docs/en/guides/sahi-tiled-inference.md +++ b/docs/en/guides/sahi-tiled-inference.md @@ -16,6 +16,17 @@ Welcome to the Ultralytics documentation on how to use YOLOv8 with [SAHI](https: SAHI (Slicing Aided Hyper Inference) is an innovative library designed to optimize object detection algorithms for large-scale and high-resolution imagery. Its core functionality lies in partitioning images into manageable slices, running object detection on each slice, and then stitching the results back together. SAHI is compatible with a range of object detection models, including the YOLO series, thereby offering flexibility while ensuring optimized use of computational resources. +

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+ Watch: Inference with SAHI (Slicing Aided Hyper Inference) using Ultralytics YOLOv8 +

+ ### Key Features of SAHI - **Seamless Integration**: SAHI integrates effortlessly with YOLO models, meaning you can start slicing and detecting without a lot of code modification.