Convert annotation formats

How To Convert Udacity TXT to Tensorflow TFRecord

In this guide, we show you how to convert data between the Udacity and TFRecord formats for free. You can use your converted data to train MobileNet SSD v2 models and other models that support the TFRecord format.

Convert with an AI agent

Paste this prompt into your coding agent

Claude Code, Cursor, Codex or any agent with the Roboflow MCP uploads your Udacity TXT dataset to Roboflow, generates a version and downloads it as Tensorflow TFRecord.

No Roboflow MCP yet? The prompt has your agent set it up first, or connect your agent before you paste it.

Rather convert it by hand? Follow the steps below

Udacity TXT

The format used by the Udacity Self Driving Car dataset.

Below, learn the structure of Udacity TXT.

udacity.txt
1478019952686311006.jpg 950 574 1004 620 0 "car"
1478019952686311006.jpg 1748 482 1818 744 0 "pedestrian"
1478019953180167674.jpg 872 586 926 632 0 "car"
1478019953689774621.jpg 686 566 728 618 1 "truck"
1478019953689774621.jpg 716 578 764 622 0 "car"
1478019953689774621.jpg 826 580 880 626 0 "car"
1478019953689774621.jpg 1540 488 1680 608 1 "car"
1478019953689774621.jpg 1646 498 1848 594 1 "car"
1478019954186238236.jpg 662 562 710 616 1 "truck"
1478019954186238236.jpg 686 576 730 628 0 "car"

Tensorflow TFRecord

Tensorflow TFRecords are a binary format used with the TensorFlow Object Detection models.

Step 1: Create a free Roboflow account

Roboflow is a universal conversion tool for computer vision annotation formats. To convert your dataset, start by creating a free Roboflow account.

Create free Roboflow account

Step 2: Upload your data into Roboflow

Once your account has been created, click Create New Project. (opens in a new tab)

Roboflow's create project form, with Object Detection selected as the project type

Upload your data to Roboflow by dragging and dropping your Udacity TXT images and annotations into the upload space.

Roboflow's upload page, with a drag-and-drop area for images, annotations, videos and PDFs

Step 3: Generate Dataset Version

Next, click "Generate New Version" to generate a new version of your dataset:

Roboflow's Generate a Dataset Version page, showing the source images and train/test split for a new version

You can then apply any preprocessing or augmentation steps to your dataset:

The augmentation step of a new dataset version, with 90° Rotate and Brightness added

Step 4: Export Dataset Version

After generating, you will be prompted to Export your dataset. You can choose to receive your dataset as a .zip file or a curl download link. Choose Tensorflow TFRecord when asked in what format you want to export your data. You will see a dropdown with various options like this:

Roboflow's Download dialog, with the export format list open and COCO highlighted

Congratulations, you have successfully converted your dataset from Udacity TXT format to Tensorflow TFRecord format!

Video Tutorial

Convert Computer Vision Annotation Formats Tutorial

Want to dive deeper into converting annotation formats with Roboflow? In the tutorial below, we explore how to convert your data in the Roboflow dashboard. We also discuss rejecting annotations and train-test-validation splits.

Frequently Asked Questions

Yes! It is free to convert Udacity TXT data into the Tensorflow TFRecord format on the Roboflow platform.

If you have between a few and a few thousand images, converting data between these formats will be quick. But, the time it takes to convert between data formats increases with the more images you have.

Show guide

Convert Udacity TXT to other formats

Convert other formats to Tensorflow TFRecord

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