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  2. Flux (text-to-image model) - Wikipedia

    en.wikipedia.org/wiki/Flux_(text-to-image_model)

    The tools consisting of Flux.1 Fill for inpainting and outpainting, Flux.1 Depth for control based on extracted depth map of input images and prompts, Flux.1 Canny for control based on extracted canny edges of input images and prompts, and Flux.1 Redux for mixing existing input images and prompts. Each tools are available in both Dev and Pro ...

  3. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    Images in 20 categories and localization bounding boxes. Labeling, bounding box included 500,000 Images, text Classification, object detection 2010 [39] [40] M. Everingham et al. CIFAR-10 Dataset Many small, low-resolution, images of 10 classes of objects. Classes labelled, training set splits created. 60,000 Images Classification 2009 [20] [41]

  4. Weka (software) - Wikipedia

    en.wikipedia.org/wiki/Weka_(software)

    H2O.ai is an open-source data science and machine learning platform; KNIME is a machine learning and data mining software implemented in Java. Massive Online Analysis (MOA) is an open-source project for large scale mining of data streams, also developed at the University of Waikato in New Zealand. Neural Designer is a data mining software based ...

  5. MNIST database - Wikipedia

    en.wikipedia.org/wiki/MNIST_database

    It was much cleaner and easier to recognize than images in SD-1. [7] It was found that machine learning systems trained and validated on SD-3 suffered significant drops in performance on the test set. [12] The original dataset from MNIST contained 128x128 binary images. Each was size-normalized to fit in a 20x20 pixel box while preserving their ...

  6. Content-based image retrieval - Wikipedia

    en.wikipedia.org/wiki/Content-based_image_retrieval

    General scheme of content-based image retrieval. Content-based image retrieval, also known as query by image content and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases (see this survey [1] for a scientific overview of the CBIR field).

  7. Orange (software) - Wikipedia

    en.wikipedia.org/wiki/Orange_(software)

    Orange is an open-source software package released under GPL and hosted on GitHub.Versions up to 3.0 include core components in C++ with wrappers in Python.From version 3.0 onwards, Orange uses common Python open-source libraries for scientific computing, such as numpy, scipy and scikit-learn, while its graphical user interface operates within the cross-platform Qt framework.

  8. Caffe (software) - Wikipedia

    en.wikipedia.org/wiki/Caffe_(software)

    Caffe supports many different types of deep learning architectures geared towards image classification and image segmentation. It supports CNN, RCNN, LSTM and fully-connected neural network designs. [8] Caffe supports GPU- and CPU-based acceleration computational kernel libraries such as Nvidia cuDNN and Intel MKL. [9] [10]

  9. waifu2x - Wikipedia

    en.wikipedia.org/wiki/Waifu2x

    waifu2x is an image scaling and noise reduction program for anime-style art and other types of photos. [1] waifu2x was inspired by Super-Resolution Convolutional Neural Network (SRCNN). [2] [3] It uses Nvidia CUDA for computing, [4] although alternative implementations that allow for OpenCL [5] and Vulkan [6] have been created.