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"
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],
"metadata": {
"id": "Phm9ccmOKye5"
}
},
{
"cell_type": "markdown",
"source": [
"## 1. Detection\n",
"\n",
"YOLO11 _detection_ models have no suffix and are the default YOLO11 models, i.e. `yolo11n.pt` and are pretrained on COCO. See [Detection Docs](https://docs.ultralytics.com/tasks/detect/) for full details.\n"
],
"metadata": {
"id": "yq26lwpYK1lq"
}
},
{
"cell_type": "code",
"source": [
"# Load YOLO11n, train it on COCO128 for 3 epochs and predict an image with it\n",
"from ultralytics import YOLO\n",
"\n",
"model = YOLO('yolo11n.pt') # load a pretrained YOLO detection model\n",
"model.train(data='coco8.yaml', epochs=3) # train the model\n",
"model('https://ultralytics.com/images/bus.jpg') # predict on an image"
],
"metadata": {
"id": "8Go5qqS9LbC5"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"## 2. Segmentation\n",
"\n",
"YOLO11 _segmentation_ models use the `-seg` suffix, i.e. `yolo11n-seg.pt` and are pretrained on COCO. See [Segmentation Docs](https://docs.ultralytics.com/tasks/segment/) for full details.\n"
],
"metadata": {
"id": "7ZW58jUzK66B"
}
},
{
"cell_type": "code",
"source": [
"# Load YOLO11n-seg, train it on COCO128-seg for 3 epochs and predict an image with it\n",
"from ultralytics import YOLO\n",
"\n",
"model = YOLO('yolo11n-seg.pt') # load a pretrained YOLO segmentation model\n",
"model.train(data='coco8-seg.yaml', epochs=3) # train the model\n",
"model('https://ultralytics.com/images/bus.jpg') # predict on an image"
],
"metadata": {
"id": "WFPJIQl_L5HT"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"## 3. Classification\n",
"\n",
"YOLO11 _classification_ models use the `-cls` suffix, i.e. `yolo11n-cls.pt` and are pretrained on ImageNet. See [Classification Docs](https://docs.ultralytics.com/tasks/classify/) for full details.\n"
],
"metadata": {
"id": "ax3p94VNK9zR"
}
},
{
"cell_type": "code",
"source": [
"# Load YOLO11n-cls, train it on mnist160 for 3 epochs and predict an image with it\n",
"from ultralytics import YOLO\n",
"\n",
"model = YOLO('yolo11n-cls.pt') # load a pretrained YOLO classification model\n",
"model.train(data='mnist160', epochs=3) # train the model\n",
"model('https://ultralytics.com/images/bus.jpg') # predict on an image"
],
"metadata": {
"id": "5q9Zu6zlL5rS"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"## 4. Pose\n",
"\n",
"YOLO11 _pose_ models use the `-pose` suffix, i.e. `yolo11n-pose.pt` and are pretrained on COCO Keypoints. See [Pose Docs](https://docs.ultralytics.com/tasks/pose/) for full details."
],
"metadata": {
"id": "SpIaFLiO11TG"
}
},
{
"cell_type": "code",
"source": [
"# Load YOLO11n-pose, train it on COCO8-pose for 3 epochs and predict an image with it\n",
"from ultralytics import YOLO\n",
"\n",
"model = YOLO('yolo11n-pose.pt') # load a pretrained YOLO pose model\n",
"model.train(data='coco8-pose.yaml', epochs=3) # train the model\n",
"model('https://ultralytics.com/images/bus.jpg') # predict on an image"
],
"metadata": {
"id": "si4aKFNg19vX"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"## 4. Oriented Bounding Boxes (OBB)\n",
"\n",
"YOLO11 _OBB_ models use the `-obb` suffix, i.e. `yolo11n-obb.pt` and are pretrained on the DOTA dataset. See [OBB Docs](https://docs.ultralytics.com/tasks/obb/) for full details."
],
"metadata": {
"id": "cf5j_T9-B5F0"
}
},
{
"cell_type": "code",
"source": [
"# Load YOLO11n-obb, train it on DOTA8 for 3 epochs and predict an image with it\n",
"from ultralytics import YOLO\n",
"\n",
"model = YOLO('yolo11n-obb.pt') # load a pretrained YOLO OBB model\n",
"model.train(data='dota8.yaml', epochs=3) # train the model\n",
"model('https://ultralytics.com/images/boats.jpg') # predict on an image"
],
"metadata": {
"id": "IJNKClOOB5YS"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "IEijrePND_2I"
},
"source": [
"# Appendix\n",
"\n",
"Additional content below."
]
},
{
"cell_type": "code",
"source": [
"# Pip install from source\n",
"!uv pip install git+https://github.com/ultralytics/ultralytics@main"
],
"metadata": {
"id": "pIdE6i8C3LYp"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# Git clone and run tests on 'main' branch\n",
"!git clone https://github.com/ultralytics/ultralytics -b main\n",
"!uv pip install -qe ultralytics"
],
"metadata": {
"id": "uRKlwxSJdhd1"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# Run tests (Git clone only)\n",
"!pytest ultralytics/tests"
],
"metadata": {
"id": "GtPlh7mcCGZX"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# Validate multiple models\n",
"for x in 'nsmlx':\n",
" !yolo val model=yolo11{x}.pt data=coco.yaml"
],
"metadata": {
"id": "Wdc6t_bfzDDk"
},
"execution_count": null,
"outputs": []
}
]
}