Standalone TFRecord reader/writer with PyTorch data loaders
-
Updated
Aug 7, 2024 - Python
Standalone TFRecord reader/writer with PyTorch data loaders
Python package to help train image classification deep neural networks for generic datasets. Especially powerful when using with TPUs. The main advantages of the package is that is leverages the tfrecords format for the data along with transfer learning and hyperparameter optimization for model training.
Fast TFRecord Reader powered by io-uring.
Fast Data Pipeline with TFRecord and io-uring
Create tf-records
Simple helper library to convert numpy data to tfrecord and build a tensorflow dataset
Automatically convert CSV or TSV files to TFRecord, and upload them to Google Cloud Storage.
End-to-End Speech Recognition Using Tensorflow
A simple example of painting color over the lips region based on facial landmark prediction with the Helen dataset, using transfer learning & fine tuning with a 3rd party pretrained model.
Import and processing of video sensor data for intake gesture recognition. Support for OREBA dataset.
Import and processing of inertial sensor data for intake gesture recognition. Support for Clemson Cafeteria, Food Intake Cycle, and OREBA datasets.
weed detection
Go library that provides easy-to-use interfaces and tools for TensorFlow users, in particular allowing to train existing TF models on .tar and .tgz datasets
TF2.0 implementation of LSTM-CRF tagger.
通过Tensorflow将Cifar10数据转换成图像,并且对图像数据序列化为tfrecord数据。本项目对tfrecord的读写操作进行了演示,对代码详细注释。代码和文档将持续更新和优化。
Add a description, image, and links to the tfrecord topic page so that developers can more easily learn about it.
To associate your repository with the tfrecord topic, visit your repo's landing page and select "manage topics."