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Fix YOLO11 usage (#17834)

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Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher 2024-11-27 14:37:25 +01:00 • committed by GitHub
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4
docs/en/integrations/albumentations.md
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@ -52,7 +52,7 @@ Now that we've covered what Albumentations is and what it can do, let's look at
### Installation
To use Albumentations with YOLOv11, start by making sure you have the necessary packages installed. If Albumentations isn't installed, the augmentations won't be applied during training. Once set up, you'll be ready to create an augmented dataset for training, with Albumentations integrated to enhance your model automatically.
To use Albumentations with YOLO11, start by making sure you have the necessary packages installed. If Albumentations isn't installed, the augmentations won't be applied during training. Once set up, you'll be ready to create an augmented dataset for training, with Albumentations integrated to enhance your model automatically.
!!! tip "Installation"
@ -67,7 +67,7 @@ For detailed instructions and best practices related to the installation process
### Usage
After installing the necessary packages, you're ready to start using Albumentations with YOLO11. When you train YOLOv11, a set of augmentations is automatically applied through its integration with Albumentations, making it easy to enhance your model's performance.
After installing the necessary packages, you're ready to start using Albumentations with YOLO11. When you train YOLO11, a set of augmentations is automatically applied through its integration with Albumentations, making it easy to enhance your model's performance.
!!! example "Usage"

8
examples/YOLO-Series-ONNXRuntime-Rust/README.md
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@ -62,7 +62,7 @@ cargo run -r -- --task detect --ver v8 --nc 6 --model xxx.onnx # YOLOv8
# Classify
cargo run -r -- --task classify --ver v5 --scale s --width 224 --height 224 --nc 1000 # YOLOv5
cargo run -r -- --task classify --ver v8 --scale n --width 224 --height 224 --nc 1000 # YOLOv8
cargo run -r -- --task classify --ver v11 --scale n --width 224 --height 224 --nc 1000 # YOLOv11
cargo run -r -- --task classify --ver v11 --scale n --width 224 --height 224 --nc 1000 # YOLO11
# Detect
cargo run -r -- --task detect --ver v5 --scale n # YOLOv5
@ -71,12 +71,12 @@ cargo run -r -- --task detect --ver v7 --scale t # YOLOv7
cargo run -r -- --task detect --ver v8 --scale n # YOLOv8
cargo run -r -- --task detect --ver v9 --scale t # YOLOv9
cargo run -r -- --task detect --ver v10 --scale n # YOLOv10
cargo run -r -- --task detect --ver v11 --scale n # YOLOv11
cargo run -r -- --task detect --ver v11 --scale n # YOLO11
cargo run -r -- --task detect --ver rtdetr --scale l # RTDETR
# Pose
cargo run -r -- --task pose --ver v8 --scale n # YOLOv8-Pose
cargo run -r -- --task pose --ver v11 --scale n # YOLOv11-Pose
cargo run -r -- --task pose --ver v11 --scale n # YOLO11-Pose
# Segment
cargo run -r -- --task segment --ver v5 --scale n # YOLOv5-Segment
@ -86,7 +86,7 @@ cargo run -r -- --task segment --ver v8 --model yolo/FastSAM-s-dyn-f16.onnx # F
# OBB
cargo run -r -- --ver v8 --task obb --scale n --width 1024 --height 1024 --source images/dota.png # YOLOv8-Obb
cargo run -r -- --ver v11 --task obb --scale n --width 1024 --height 1024 --source images/dota.png # YOLOv11-Obb
cargo run -r -- --ver v11 --task obb --scale n --width 1024 --height 1024 --source images/dota.png # YOLO11-Obb
```
**`cargo run -- --help` for more options**