Showing 4 open source projects for "image search algorithm"

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    Imagen - Pytorch

    Imagen - Pytorch

    Implementation of Imagen, Google's Text-to-Image Neural Network

    Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior...
    Downloads: 3 This Week
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  • 2
    CNN for Image Retrieval
    cnn-for-image-retrieval is a research-oriented project that demonstrates the use of convolutional neural networks (CNNs) for image retrieval tasks. The repository provides implementations of CNN-based methods to extract feature representations from images and use them for similarity-based retrieval. It focuses on applying deep learning techniques to improve upon traditional handcrafted descriptors by learning features directly from data. The code includes training and evaluation scripts that...
    Downloads: 12 This Week
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  • 3
    algo

    algo

    50 Code Implementations You Must Know About Data Structures

    algo is an educational repository containing practical implementations of essential data structures and algorithms. It organizes roughly fifty core exercises by topic rather than presenting a single reusable software library. The material covers arrays, linked lists, stacks, queues, recursion, sorting, binary search, hash tables, strings, trees, heaps, and graphs. More advanced examples address backtracking, divide-and-conquer methods, dynamic programming, shortest paths, topological...
    Downloads: 2 This Week
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  • 4
    Solid Python

    Solid Python

    A comprehensive gradient-free optimization framework written in Python

    Solid is a Python framework for gradient-free optimization. It contains basic versions of many of the most common optimization algorithms that do not require the calculation of gradients, and allows for very rapid development using them.
    Downloads: 1 This Week
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