The Tensorflow Object Detection API uses a proprietary binary file format called TFRecord. Creating TFRecord files has long been the bane of many developers' existence. While they are very efficient for TensorFlow's deep learning framework to parse, they are quite opaque and are not human readable. They're quite finicky; If something is wrong, it's not easy to find out why.
It's not really possible to create these files by hand. You'll need to use a tool to create them. The most foolproof tool to use is Roboflow because, unlike most one-off shell scripts, Roboflow is a universal converter for computer vision formats.
With Roboflow you can seamlessly convert whatever filetype your annotation tool exports directly into a TFRecord that's ready to use for training your model.
Below, learn the structure of Tensorflow TFRecord.
With Roboflow supervision, an open source Python package with utilities for completing computer vision tasks, you can merge and split detections in Tensorflow TFRecord. Read our dedicated guides to learn how to merge and split Tensorflow TFRecord detections.
Below, see model architectures that require data in the Tensorflow TFRecord format when training a new model.
On each page below, you can find links to our guides that show how to plot predictions from the model, and complete other common tasks like detecting small objects with the model.
The Tensorflow Object Detection API uses a proprietary binary file format called TFRecord. Creating TFRecord files has long been the bane of many developers' existence. While they are very efficient for TensorFlow's deep learning framework to parse, they are quite opaque and are not human readable. They're quite finicky; If something is wrong, it's not easy to find out why.
It's not really possible to create these files by hand. You'll need to use a tool to create them. The most foolproof tool to use is Roboflow because, unlike most one-off shell scripts, Roboflow is a universal converter for computer vision formats.
With Roboflow you can seamlessly convert whatever filetype your annotation tool exports directly into a TFRecord that's ready to use for training your model.
With Roboflow, you can deploy a computer vision model without having to build your own infrastructure.
Below, we show how to convert data to and from
Tensorflow TFRecord
. We also list popular models that use the
Tensorflow TFRecord
data format. Our conversion tools are free to use.
Free data conversion
SOC II Type 2 Compliant
Trusted by 250,000+ developers
Free data conversion
SOC II Type 1 Compliant
Trusted by 250,000+ developers
The
MobileNet SSD v2
,
Faster R-CNN
,
EfficientDet (D7) Tensorflow 2
,
models all use the
data format.