There are 5 repositories under image-augmentation topic.
Image augmentation for machine learning experiments.
Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
List of useful data augmentation resources. You will find here some not common techniques, libraries, links to GitHub repos, papers, and others.
Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)
Data Science Hacks consists of tips, tricks to help you become a better data scientist. Data science hacks are for all - beginner to advanced. Data science hacks consist of python, jupyter notebook, pandas hacks and so on.
Artificial Intelligence Learning Notes.
AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/
A simpler way of reading and augmenting image segmentation data into TensorFlow
WB color augmenter improves the accuracy of image classification and image semantic segmentation methods by emulating different WB effects (ICCV 2019) [Python & Matlab].
A fast image augmentation library in Julia for machine learning.
A fast tool to do image augmentation on GPU(especially elastic_deform), can be helpful to research on Medical Image.
Image augmentation for computer vision
Deep Learning for Automatic Pneumonia Detection, RSNA challenge
Custom image data generator for TF Keras that supports the modern augmentation module albumentations
MemeGen is a web application where the user gives an image as input and our tool generates a meme at one click for the user.
A Traffic Sign Recognition Project which can help the driver recognise the signs via text as well as audio. Can be used at Night also.
Image data augmentation on-the-fly by add new class on transforms in PyTorch and torchvision.
A python library for instagram filters
Run 3 scripts to (1) Synthesize images (by putting few template images onto backgrounds), (2) Train YOLOv3, and (3) Detect objects for: one image, images, video, webcam, or ROS topic.
Automatic License Plate Recognition for Traffic Violation Management made with YOLOv4, Darknet, Tensorflow Lite
Image augmentation with simultaneous transformation of keypoints, bounding boxes, and segmentation mask
discolight is a robust, flexible and infinitely hackable library for generating image augmentations ✨
Methods for alignment of global image statistics aimed at unsupervised Domain Adaptation and Data Augmentation
TensorFlow2+ graph image augmentation library optimized for tf.data.Dataset.
This repository is containing an object classification & localization project for SINGLE object.
HistoClean is a tool for the preprocessing and augmentation of images used in deep learning models. This easy to use application brings together the most popular image processing packages from across the python universe, meaning no more looking at documentation! HistoClean provides real time feedback to augmentations and preprocessing options. This allows users to evaluate their steps before implementation.
This repository contains the jupyter notebooks for the custom-built DenseNet Model build on Tiny ImageNet dataset
Pytorch implements yolov3.Good performance, easy to use, fast speed.
Chechink the performance of different augmentation techniques on the BraTS 2020 data.
Optimize RandAugment with differentiable operations
Object detection and instance segmentation on MaskRCNN with torchvision, albumentations, tensorboard and cocoapi. Supports custom coco datasets with positive/negative samples.
Image rotation and cropping out the black borders in TensorFlow
SuperpixelGridMasks is an approach for sensor-based data augmentation towards image classification tasks and so on.
Code for the implemenation of the Patch Augmentation technique