Standalone TFRecord reader/writer with PyTorch data loaders
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Updated
Aug 20, 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.
This project aims to use artificial intelligence-based object detection technology to contribute to the conservation and preservation of manta rays, sharks, and sea turtles in the Caribbean Sea. 🌊
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.
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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.
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