Data/Image Augmentation
Machine learning applications especially in deep learning domain continue to diversify and increase rapidly. Data augmentation techniques may be a good tool against challenges which artificial intelligence world faces.
Data augmentation is useful to improve performance and outcomes of machine learning models by forming new and different examples to train datasets. If dataset in a machine learning model is rich and sufficient, the model performs better and more accurate.
For machine learning models, collecting and labeling of data can be exhausting and costly processes. Transformations in datasets by using data augmentation techniques allow companies to reduce these operational costs.
What is Image Augmentation
Image augmentation is a technique of altering the existing data to create some more data for the model training process. In other words, it is the process of artificially expanding the available dataset for training a deep learning model.
What is NEUY Augmentation
NEUY Augmentation is a super fast and efficient AI image dataset augmentation tool that will help you build better models as well as utilize less system resources during testing and training sessions.
Storage is extremely cheap relative to CPU, GPU or memory resources. By separating the image augmentation processing of model creation from the actual code in python or your preferred tool and make it a single upfront processing cost, your actual model code can be dedicated to training.
– Multi-Threaded
– Support for +30 image file formats
– Support for +18 digital camera formats
– Output in JPG for speed and TIFF for quality preserving
– +14 Image Transformation or Distortions (utilizing Anti-Alias, Bicubic and Lanczos)
– 15 High Quality Image Filters
– Output sizes in 256,512,1024,2048,4096 and Original
Convert a single image into +250 variants, from a dataset of 100 images to 25000 in seconds.
App download will be available in MacOS App store soon, pending approval.
Feature Requests
We have +100 potential image augmentations available to us, so rather than doing a complete feature dump. We wanted you to tell us what we should add to help your next AI project. Feature Request Form
