Search Results for "base64 image decoder"
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Showing 76 open source projects for "base64 image decoder"
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1
Generic Image Decoder
A standalone, portable generic Ada package for decoding images
The Generic Image Decoder is a package for decoding a broad variety of image formats, from any data stream, to any kind of medium. Unconditionally portable code: OS-, CPU-, compiler- independent code. More information on... http://gen-img-dec.sf.net Alire crate: https://alire.ada.dev/crates/gid Mirror: https://github.com/zertovitch/gid -
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Step1X-Edit
A SOTA open-source image editing model
Step1X-Edit is a state-of-the-art open-source image editing model/framework that uses a multimodal large language model (LLM) together with a diffusion-based image decoder to let users edit images simply via natural-language instructions plus a reference image. You supply an existing image and a textual command — e.g. “add a ruby pendant on the girl’s neck” or “make the background a sunset over mountains” — and the model interprets the instruction, computes a latent embedding combining the image content and user intent, then decodes a new image implementing the edit. ... -
3
Segment Anything
Provides code for running inference with the SegmentAnything Model
Segment Anything (SAM) is a foundation model for image segmentation that’s designed to work “out of the box” on a wide variety of images without task-specific fine-tuning. It’s a promptable segmenter: you guide it with points, boxes, or rough masks, and it predicts high-quality object masks consistent with the prompt. The architecture separates a powerful image encoder from a lightweight mask decoder, so the heavy vision work can be computed once and the interactive part stays fast. ... -
4
OpenAI DALL·E AsyncImage SwiftUI
OpenAI swift async text to image for SwiftUI app using OpenAI
...It uses diffusion models for both the model's prior (which produces an image embedding given a text caption) and the decoder that generates the final image. In machine learning, diffusion models, also known as diffusion probabilistic models, are a class of latent variable models. They are Markov chains trained using variational inference. The goal of diffusion models is to learn the latent structure of a dataset by modeling the way in which data points diffuse through the latent space. -
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AV1 AVIF
AV1 Image File Format Specification - ISO-BMFF/HEIF derivative
AV1 AVIF is the official specification and reference design for the AV1 Image File Format (AVIF), defining how AV1-encoded bitstreams are packaged into the HEIF container format (based on ISOBMFF) to produce AVIF files. The project outlines the syntax and semantics required for AVIF compliance, including support for multiple image profiles, color depths, chroma subsampling modes, HDR/WCG, alpha channels, animation/image sequences, and various color-space/bit-depth combinations — making AVIF... -
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x-transformers
A simple but complete full-attention transformer
A simple but complete full-attention transformer with a set of promising experimental features from various papers. Proposes adding learned memory key/values prior to attending. They were able to remove feedforwards altogether and attain a similar performance to the original transformers. I have found that keeping the feedforwards and adding the memory key/values leads to even better performance. Proposes adding learned tokens, akin to CLS tokens, named memory tokens, that is passed through... -
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GitHub Actions for Firebase
GitHub Action for interacting with Firebase
...A normal service account key(json format) or a base64 encoded service account key with the needed permissions for what you are trying to deploy/update. If you're deploying functions, you would also need the Cloud Functions Developer role, and the Cloud Scheduler Admin for scheduled functions. -
8
Wuffs
Wrangling Untrusted File Formats Safely
Wuffs is a memory-safe, zero-dependency library and domain-specific language for writing high-performance image codecs and related parsers. Instead of trusting ad-hoc C, Wuffs code is compiled to C with strong bounds, integer, and state checks inserted by construction, aiming to eliminate whole classes of security bugs without a heavy runtime. The design prioritizes predictable performance: decoders avoid dynamic allocation by default, return explicit “short read” signals, and run well in... -
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HTTP Shortcuts for Android
Android app to create home screen shortcuts
A simple Android app that allows you to create shortcuts that can be placed on your home screen. Each shortcut, when clicked, triggers an HTTP request, with the possibility to process and display the response in various ways. Run arbitrary JavaScript before & after execution, which allows for lots of customization with features such as compute values such as timestamps, random numbers, UUIDs, hashes, HMACs, base64, etc. Parse JSON or XML and extract data from them. Show toast message or... -
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10
DocArray
The data structure for multimodal data
DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API. Door to multimodal world: super-expressive data structure for representing complicated/mixed/nested text, image, video, audio, 3D mesh data. The foundation data structure of Jina, CLIP-as-service, DALL·E Flow, DiscoArt etc. ... -
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Segmentation Models
Segmentation models with pretrained backbones. PyTorch
...Preparing your data the same way as during weights pre-training may give you better results (higher metric score and faster convergence). It is not necessary in case you train the whole model, not only the decoder. Pytorch Image Models (a.k.a. timm) has a lot of pretrained models and interface which allows using these models as encoders in smp, however, not all models are supported. Input channels parameter allows you to create models, which process tensors with an arbitrary number of channels. -
12
Bard API
The unofficial python package that returns response of Google Bard
The Python package returns a response of Google Bard through the value of the cookie. This package is designed for application to the Python package ExceptNotifier and Co-Coder. Please note that the bardapi is not a free service, but rather a tool provided to assist developers with testing certain functionalities due to the delayed development and release of Google Bard's API. It has been designed with a lightweight structure that can easily adapt to the emergence of an official API.... -
13
DALL-E 2 - Pytorch
Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis
...To train CLIP, you can either use x-clip package, or join the LAION discord, where a lot of replication efforts are already underway. Then, you will need to train the decoder, which learns to generate images based on the image embedding coming from the trained CLIP. -
14
PNMViewer
Rudimentary PNM image viewer using Simple DirectMedia Layer library
This project is only a proof-of-concept to serve as an illustration how to combine the Simple DirectMedia Layer library (SDL) with a custom image decoder but with only one memory allocation instead of multiple operations. For a complete implementation, see NetPBM image library: https://netpbm.sourceforge.net/ -
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SafeUtils
110+ developer tools as native MacOS, Linux & Windows desktop apps.
Tools: https://safeutils.com/barcode-generator https://safeutils.com/color-picker https://safeutils.com/qr-code-generator https://safeutils.com/qr-code-scanner https://safeutils.com/word-counter https://safeutils.com/base-64-decoder https://safeutils.com/diff-checker https://safeutils.com/hex-to-ascii https://safeutils.com/json-formatter https://safeutils.com/lorem-ipsum-generator https://safeutils.com/random-generator https://safeutils.com/time-converter https://safeutils.com/... -
16
LittleFancyTool
supports RS232/485/Modbus, sockets, text enc/dec (multi-alg) and so on
This small tool, built with WinForm and Ant Design UI, supports RS232, RS485, and Modbus serial communication debugging, socket communication capabilities, multi-algorithm text encryption/decryption, image/text Base64 conversion, and asynchronous multi-threaded file encryption/decryption. -
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Float-ditherer
A dithering software based around floats
Float-ditherer is a tool that converts images into pure 1-bit images using a user specified palette tailored to convert images,textures and sprites using a float-based sampling method and float matrix. The software is meant to be lightweight and for power-users -
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Blaiz Tools
Tools for working with Gossamer codebase and app source code
Tools for packing files, converting images, manipulating text, checking code and working with the Gossamer codebase and app source code. -
19
faxcoder
Tools to access streams in PDF-files at the object level.
faxcoder A C tools to access streams in PDF-files at the object level. License: GNU Lesser GPL This project includes two tools: faxg4coder - a G3/G4 Fax En-/Decoder faxlzwcoder - a (TIFF) LZW En-/Decoder -
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DevToys
A Swiss Army knife for developers
DevToys helps in daily tasks like formatting JSON, comparing text, testing RegExp. No need to use many untruthful websites to do simple tasks with your data. With Smart Detection, DevToys is able to detect the best tool that can treat the data you copied in the clipboard of your Windows. Compact overlay lets you keep the app in small and on top of other windows. Multiple instances of the app can be used at once. DevToys works entirely offline, meaning that none of the data used by the app... -
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PNG_IO
An Ada 2012 library for reading and writing PNG image files
PNG_IO is an Ada2012 coder/decoder for Portable Network Graphics, allowing Ada2012 programs to read and write PNG files. It is portable across machines and operating systems. It depends on Zlib and Zlib_Ada to perform lossless compression and decompression. Versions prior to v5 were in Ada95. -
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Karlo
Text-conditional image generation model based on OpenAI's unCLIP
Karlo is a text-conditional image generation model based on OpenAI's unCLIP architecture with the improvement over the standard super-resolution model from 64px to 256px, recovering high-frequency details only in the small number of denoising steps. We train all components from scratch on 115M image-text pairs including COYO-100M, CC3M, and CC12M. In the case of Prior and Decoder, we use ViT-L/14 provided by OpenAI’s CLIP repository. -
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MAE (Masked Autoencoders)
PyTorch implementation of MAE
MAE (Masked Autoencoders) is a self-supervised learning framework for visual representation learning using masked image modeling. It trains a Vision Transformer (ViT) by randomly masking a high percentage of image patches (typically 75%) and reconstructing the missing content from the remaining visible patches. This forces the model to learn semantic structure and global context without supervision. The encoder processes only the visible patches, while a lightweight decoder reconstructs the full image—making pretraining computationally efficient. ... -
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Deep learning time series forecasting
Deep learning PyTorch library for time series forecasting
...Historically, this repository provided open-source benchmarks and codes for flash flood and river flow forecasting. Full transformer (SimpleTransformer in model_dict): The full original transformer with all 8 encoder and decoder blocks. Requires passing the target in at inference. -
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UpscalerJS
Image Upscaling in Javascript. Increase image resolution up to 4x
Image Upscaling in Javascript. Increase image resolution up to 4x using Tensorflow.js. Open source, browser/Node compatibility, and completely free to use under the MIT license. Scale images up to 4x their original size, all in Javascript. UpscalerJS ships with pre-trained models in the box covering a wide variety of use cases. Or bring your own!
