# Writing Custom Dataset Exporters This recipe demonstrates how to write a [custom DatasetExporter](https://voxel51.com/docs/fiftyone/user_guide/export_datasets.html#custom-formats) and use it to export a FiftyOne dataset to disk in your custom format. ## Setup If you haven’t already, install FiftyOne: In this recipe we’ll use the [FiftyOne Dataset Zoo](https://docs.voxel51.com/dataset_zoo/index.html) to download the [CIFAR-10 dataset](https://www.cs.toronto.edu/~kriz/cifar.html) to use as sample data to feed our custom exporter. Behind the scenes, FiftyOne uses either the [TensorFlow Datasets](https://www.tensorflow.org/datasets) or [TorchVision Datasets](https://pytorch.org/vision/stable/datasets.html) libraries to wrangle the datasets, depending on which ML library you have installed. You can, for example, install PyTorch as follows: ## Writing a DatasetExporter FiftyOne provides a [DatasetExporter](https://voxel51.com/docs/fiftyone/api/fiftyone.utils.data.html#fiftyone.utils.data.exporters.DatasetExporter) interface that defines how it exports datasets to disk when methods such as [Dataset.export()](https://voxel51.com/docs/fiftyone/api/fiftyone.core.html#fiftyone.core.dataset.Dataset.export) are used. `DatasetExporter` itself is an abstract interface; the concrete interface that you should implement is determined by the type of dataset that you are exporting. See [writing a custom DatasetExporter](https://voxel51.com/docs/fiftyone/user_guide/export_datasets.html#custom-formats) for full details. In this recipe, we’ll write a custom [LabeledImageDatasetExporter](https://voxel51.com/docs/fiftyone/api/fiftyone.utils.data.html#fiftyone.utils.data.exporters.LabeledImageDatasetExporter) that can export an image classification dataset to disk in the following format: ```none / data/ . . ... labels.csv ``` where `labels.csv` is a CSV file that contains the image metadata and associated labels in the following format: ```none filepath,size_bytes,mime_type,width,height,num_channels,label ,,,,,, ,,,,,, ... ``` Here’s the complete definition of the `DatasetExporter`: ## Generating a sample dataset In order to use `CSVImageClassificationDatasetExporter`, we need some labeled image samples to work with. Let’s use some samples from the test split of CIFAR-10: ## Exporting a dataset With our samples and `DatasetExporter` in-hand, exporting the samples to disk in our custom format is as simple as follows: Let’s inspect the contents of the exported dataset to verify that it was written in the correct format: ## Cleanup You can cleanup the files generated by this recipe by running: