diff --git a/examples/tutorial.ipynb b/examples/tutorial.ipynb index 6a05261..82d524d 100644 --- a/examples/tutorial.ipynb +++ b/examples/tutorial.ipynb @@ -57,9 +57,10 @@ "metadata": { "id": "wbvMlHd_QwMG", "colab": { - "base_uri": "https://localhost:8080/" + "base_uri": "https://localhost:8080/", + "height": 1000 }, - "outputId": "d7b7b0a6-6a29-4e6d-e404-8d67d2be86e2" + "outputId": "19bbf989-d9fa-419d-8948-aaba39db8ddb" }, "source": [ "# Pip install method (recommended)\n", @@ -67,14 +68,14 @@ "import ultralytics\n", "ultralytics.checks()" ], - "execution_count": null, + "execution_count": 1, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ - "Ultralytics YOLOv8.0.1 🚀 Python-3.8.16 torch-1.13.0+cu116 CUDA:0 (Tesla T4, 15110MiB)\n", - "Setup complete ✅ (2 CPUs, 12.7 GB RAM, 23.1/78.2 GB disk)\n" + "Ultralytics YOLOv8.0.4 🚀 Python-3.8.16 torch-1.13.1+cu116 CUDA:0 (Tesla T4, 15110MiB)\n", + "Setup complete ✅ (2 CPUs, 12.7 GB RAM, 23.0/166.8 GB disk)\n" ] } ] @@ -100,7 +101,7 @@ "source": [ "# 1. Predict\n", "\n", - "YOLOv8 may be used directly in the Command Line Interface (CLI) with a `yolo` command. `yolo` can be used for a variety of tasks and modes and accepts additional arguments, i.e. `imgsz=640`. See a full list of available `yolo` [arguments](https://docs.ultralytics.com/config/) in the YOLOv8 [Docs](https://docs.ultralytics.com).\n" + "YOLOv8 may be used directly in the Command Line Interface (CLI) with a `yolo` command for a variety of tasks and modes and accepts additional arguments, i.e. `imgsz=640`. See a full list of available `yolo` [arguments](https://docs.ultralytics.com/config/) in the YOLOv8 [Docs](https://docs.ultralytics.com).\n" ] }, { @@ -154,7 +155,7 @@ }, "source": [ "# 2. Val\n", - "Validate a model's accuracy on the [COCO](https://cocodataset.org/#home) dataset's `val` or `test` splits. The latest YOLOv8 [models](https://github.com/ultralytics/ultralytics/releases) are downloaded automatically the first time they are used." + "Validate a model's accuracy on the [COCO](https://cocodataset.org/#home) dataset's `val` or `test` splits. The latest YOLOv8 [models](https://github.com/ultralytics/ultralytics#models) are downloaded automatically the first time they are used." ] }, { @@ -290,7 +291,7 @@ "\n", "

\n", "\n", - "Train YOLOv8 on detection, segmentation and classification datasets." + "Train YOLOv8 on [Detection](https://docs.ultralytics.com/tasks/detection/), [Segmentation](https://docs.ultralytics.com/tasks/detection/) and [Classification](https://docs.ultralytics.com/tasks/detection/) datasets." ] }, { @@ -461,20 +462,22 @@ "\n", "Export a YOLOv8 model to any supported format with the `format` argument, i.e. `format=onnx`.\n", "\n", - "Format | `format=...**bold text**` | Model\n", - "--- | --- | ---\n", - "PyTorch | - | yolov8n.pt\n", - "TorchScript | `torchscript` | yolov8n.torchscript\n", - "ONNX | `onnx` | yolov8n.onnx\n", - "OpenVINO | `openvino` | yolov8n_openvino_model/\n", - "TensorRT | `engine` | yolov8n.engine\n", - "CoreML | `coreml` | yolov8n.mlmodel\n", - "TensorFlow SavedModel | `saved_model` | yolov8n_saved_model/\n", - "TensorFlow GraphDef | `pb` | yolov8n.pb\n", - "TensorFlow Lite | `tflite` | yolov8n.tflite\n", - "TensorFlow Edge TPU | `edgetpu` | yolov8n_edgetpu.tflite\n", - "TensorFlow.js | `tfjs` | yolov8n_web_model/\n", - "PaddlePaddle | `paddle` | yolov8n_paddle_model/" + "\n", + "| Format | `format=` | Model |\n", + "|----------------------------------------------------------------------------|--------------------|---------------------------|\n", + "| [PyTorch](https://pytorch.org/) | - | `yolov8n.pt` |\n", + "| [TorchScript](https://pytorch.org/docs/stable/jit.html) | `torchscript` | `yolov8n.torchscript` |\n", + "| [ONNX](https://onnx.ai/) | `onnx` | `yolov8n.onnx` |\n", + "| [OpenVINO](https://docs.openvino.ai/latest/index.html) | `openvino` | `yolov8n_openvino_model/` |\n", + "| [TensorRT](https://developer.nvidia.com/tensorrt) | `engine` | `yolov8n.engine` |\n", + "| [CoreML](https://github.com/apple/coremltools) | `coreml` | `yolov8n.mlmodel` |\n", + "| [TensorFlow SavedModel](https://www.tensorflow.org/guide/saved_model) | `saved_model` | `yolov8n_saved_model/` |\n", + "| [TensorFlow GraphDef](https://www.tensorflow.org/api_docs/python/tf/Graph) | `pb` | `yolov8n.pb` |\n", + "| [TensorFlow Lite](https://www.tensorflow.org/lite) | `tflite` | `yolov8n.tflite` |\n", + "| [TensorFlow Edge TPU](https://coral.ai/docs/edgetpu/models-intro/) | `edgetpu` | `yolov8n_edgetpu.tflite` |\n", + "| [TensorFlow.js](https://www.tensorflow.org/js) | `tfjs` | `yolov8n_web_model/` |\n", + "| [PaddlePaddle](https://github.com/PaddlePaddle) | `paddle` | `yolov8n_paddle_model/` |\n", + "\n" ], "metadata": { "id": "nPZZeNrLCQG6" @@ -540,7 +543,7 @@ "results = model.train(data='coco128.yaml', epochs=3) # train the model\n", "results = model.val() # evaluate model performance on the validation set\n", "results = model('https://ultralytics.com/images/bus.jpg') # predict on an image\n", - "success = YOLO('yolov8n.pt').export(format='onnx') # export a model to ONNX format" + "success = model.export(format='onnx') # export the model to ONNX format" ], "metadata": { "id": "bpF9-vS_DAaf" @@ -553,7 +556,9 @@ "source": [ "# 6. Tasks\n", "\n", - "YOLOv8 can train, val, predict and export models for the 3 primary tasks in vision AI: detection, segmentation and classification." + "YOLOv8 can train, val, predict and export models for the 3 primary tasks in vision AI: detection, segmentation and classification.\n", + "\n", + "\n" ], "metadata": { "id": "Phm9ccmOKye5" @@ -564,7 +569,7 @@ "source": [ "## 1. Detection\n", "\n", - "Detection models have no suffix and are the default YOLOv8 models, i.e. `yolov8n.pt`" + "YOLOv8 _detection_ models have no suffix and are the default YOLOv8 models, i.e. `yolov8n.pt` and are pretrained on COCO. See [Detection Docs](https://docs.ultralytics.com/tasks/detection/) for full details.\n" ], "metadata": { "id": "yq26lwpYK1lq" @@ -591,7 +596,7 @@ "source": [ "## 2. Segmentation\n", "\n", - "Segmentation models use the `-seg` suffix, i.e. `yolov8n-seg.pt`" + "YOLOv8 _segmentation_ models use the `-seg` suffix, i.e. `yolov8n-seg.pt` and are pretrained on COCO. See [Segmentation Docs](https://docs.ultralytics.com/tasks/segmentation/) for full details.\n" ], "metadata": { "id": "7ZW58jUzK66B" @@ -618,7 +623,7 @@ "source": [ "## 3. Classification\n", "\n", - "Classification models use the `-cls` suffix, i.e. `yolov8n-cls.pt`" + "YOLOv8 _classification_ models use the `-cls` suffix, i.e. `yolov8n-cls.pt` and are pretrained on ImageNet. See [Classification Docs](https://docs.ultralytics.com/tasks/detection/) for full details.\n" ], "metadata": { "id": "ax3p94VNK9zR"