There are 1 repository under tfrecords topic.
TensorFlow template application for deep learning
Handwritten Korean Character Recognition with TensorFlow and Android
TFRecorder makes it easy to create TensorFlow records (TFRecords) from Pandas DataFrames and CSVs files containing images or structured data.
Feed your own image data to a pre-trained network by tensorflow
tensorflow prediction using c++ api
Pytorch and TensorFlow data loaders for several audio datasets
A one stop shop for all of your activity recognition needs.
Data Reading Blocks for Python
Try to use tf.estimator and tf.data together to train a cnn model.
Extending Keras to support tfrecord dataset
TensorFlow Input Pipeline Examples based on multi-thread and FIFOQueue
Train a 4-layer Convolutional Neural Network to detect trigger word
parse WIDER FACE dataset to tensorflow tfrecord format for object detection api
tensorflow object detection api helper tool ( custom object detection )
This Repo contains the updated implementation of our paper "Weakly supervised 3D classification of chest CT using aggregated multi-resolution deep segmentation features", Proc. SPIE 11314, Medical Imaging 2020: Computer-Aided Diagnosis, 1131408 (16 March 2020)
Sparse learning in TensorFlow using data acquired from Spark.
A course project that detect cells in image by a simple full convolution neural network. The project is driven by TensorFlow.
Implement lenet and vgg19 by tensorflow with dataset mnist using tfrecord
This is my first Internship Project on Deep Learning. This is a challenge of WIDER Face Benchmark whose aim is to detect faces in the images in any condition of various poses, illuminations and occlusions. And we managed to get the accuracy of 91% in detecting every type of images.
A tensorflow batteries included kit to write tensorflow networks from scratch or use existing ones.
Face recognition using Tensorflow
Object detection and recognition for blind person using Raspberry Pi
Read your tfrecord files from the command line
Dataset-convertor tool in python for object detection dataset
GCS specific notebooks and scripts to download VOC 2007, COCO 2017 and DIV2K Datasets and create TFRecords.
:floppy_disk: :fire: The fastest and easiest to use TFRecords formatter
A pure Julia implementation to read/write TFRecord
The main problem of conditional text generation is that it is mainly based on the content of an input set of examples: this leads to little diversification of the generated text. To overcome this shortcoming, we have fine tuned CTRL using three different datasets. The first model has been used as a baseline for comparison, while the other two have been used to obtain more formal and informal text. The BART model has been employed for text classification to gauge formality.
Follow Official Tensorflow's retrain.py, which is an example script that shows how one can adapt a pretrained network for other classification problems. This repository improved with quick data read and process to make the training more efficient.