# Object Detection - TensorFlow
<a name="object-detection-tensorflow"></a>

The Amazon SageMaker AI Object Detection - TensorFlow algorithm is a supervised learning algorithm that supports transfer learning with many pretrained models from the [TensorFlow Model Garden](https://github.com/tensorflow/models). Use transfer learning to fine-tune one of the available pretrained models on your own dataset, even if a large amount of image data is not available. The object detection algorithm takes an image as input and outputs a list of bounding boxes. Training datasets must consist of images in .`jpg`, `.jpeg`, or `.png` format. This page includes information about Amazon EC2 instance recommendations and sample notebooks for Object Detection - TensorFlow.

**Topics**
+ [How to use the SageMaker AI Object Detection - TensorFlow algorithm](object-detection-tensorflow-how-to-use.md)
+ [Input and output interface for the Object Detection - TensorFlow algorithm](object-detection-tensorflow-inputoutput.md)
+ [Amazon EC2 instance recommendation for the Object Detection - TensorFlow algorithm](#object-detection-tensorflow-instances)
+ [Object Detection - TensorFlow sample notebooks](#object-detection-tensorflow-sample-notebooks)
+ [How Object Detection - TensorFlow Works](object-detection-tensorflow-HowItWorks.md)
+ [TensorFlow Models](object-detection-tensorflow-Models.md)
+ [Object Detection - TensorFlow Hyperparameters](object-detection-tensorflow-Hyperparameter.md)
+ [Tune an Object Detection - TensorFlow model](object-detection-tensorflow-tuning.md)

## Amazon EC2 instance recommendation for the Object Detection - TensorFlow algorithm
<a name="object-detection-tensorflow-instances"></a>

The Object Detection - TensorFlow algorithm supports all GPU instances for training, including:
+ `ml.p2.xlarge`
+ `ml.p2.16xlarge`
+ `ml.p3.2xlarge`
+ `ml.p3.16xlarge`

We recommend GPU instances with more memory for training with large batch sizes. Both CPU (such as M5) and GPU (P2 or P3) instances can be used for inference. For a comprehensive list of SageMaker training and inference instances across AWS Regions, see [Amazon SageMaker Pricing](https://aws.amazon.com/sagemaker/pricing/).

## Object Detection - TensorFlow sample notebooks
<a name="object-detection-tensorflow-sample-notebooks"></a>

For more information about how to use the SageMaker AI Object Detection - TensorFlow algorithm for transfer learning on a custom dataset, see the [Introduction to SageMaker TensorFlow - Object Detection](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/object_detection_tensorflow/Amazon_Tensorflow_Object_Detection.ipynb) notebook.

For instructions how to create and access Jupyter notebook instances that you can use to run the example in SageMaker AI, see [Amazon SageMaker notebook instances](nbi.md). After you have created a notebook instance and opened it, select the **SageMaker AI Examples** tab to see a list of all the SageMaker AI samples. To open a notebook, choose its **Use** tab and choose **Create copy**.