textaugment
tfops-aug
| textaugment | tfops-aug | |
|---|---|---|
| 2 | 1 | |
| 372 | 14 | |
| 1.3% | - | |
| 4.6 | 4.9 | |
| 2 months ago | over 1 year ago | |
| Python | Python | |
| MIT License | MIT License |
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textaugment
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NLP augmentation models
I just came across this Python library. It has a bunch of dictionary-, backtranslation- and knowledge-based heuristics that should work most of the time:
- Prefer volume or quality for BERT-based Text classification model
tfops-aug
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tfops-aug: Lightweight and fast image augmentation library based on TensorFlow Ops
With tfops-aug, you can easily apply an augmentation policy to your images, including shearing, translations, random gamma, random color shifts, solarization, posterization, histogram equalization, and more. The library is fully compatible with Tensorflow's data pipelines, so you can easily integrate it into your existing projects. And because it uses only Tensorflow operations, it's fast and efficient and can be directly applied on a tf.Tensor of type tf.uint8.
What are some alternatives?
AugLy - A data augmentations library for audio, image, text, and video.
tensorflow-yolov4-tflite - YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
word_forms - Accurately generate all possible forms of an English word e.g "election" --> "elect", "electoral", "electorate" etc.
yolov4-custom-functions - A Wide Range of Custom Functions for YOLOv4, YOLOv4-tiny, YOLOv3, and YOLOv3-tiny Implemented in TensorFlow, TFLite, and TensorRT.
scattertext - Beautiful visualizations of how language differs among document types.
mastercomfig - A modern customization framework for Team Fortress 2
wordnet - Stand-alone WordNet API
seed_rl - SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.
magnitude - A fast, efficient universal vector embedding utility package.
Fast-SRGAN - A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps
tf-explain - Interpretability Methods for tf.keras models with Tensorflow 2.x