Search Results for "clip"
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Showing 13 open source projects for "clip"
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Multimodal
TorchMultimodal is a PyTorch library
...The library provides modular building blocks such as encoders, fusion modules, loss functions, and transformations that support combining modalities (vision, text, audio, etc.) in unified architectures. It includes a collection of ready model classes—like ALBEF, CLIP, BLIP-2, COCA, FLAVA, MDETR, and Omnivore—that serve as reference implementations you can adopt or adapt. The design emphasizes composability: you can mix and match encoder, fusion, and decoder components rather than starting from monolithic models. The repository also includes example scripts and datasets for common multimodal tasks (e.g. retrieval, visual question answering, grounding) so you can test and compare models end to end. ... -
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ComfyUI
The most powerful and modular diffusion model GUI, api and backend
The most powerful and modular diffusion model is GUI and backend. This UI will let you design and execute advanced stable diffusion pipelines using a graph/nodes/flowchart-based interface. We are a team dedicated to iterating and improving ComfyUI, supporting the ComfyUI ecosystem with tools like node manager, node registry, cli, automated testing, and public documentation. Open source AI models will win in the long run against closed models and we are only at the beginning. Our core mission... -
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AUTOMATIC1111 Stable Diffusion web UI
Stable Diffusion web UI
AUTOMATIC1111's stable-diffusion-webui is a powerful, user-friendly web interface built on the Gradio library that allows users to easily interact with Stable Diffusion models for AI-powered image generation. Supporting both text-to-image (txt2img) and image-to-image (img2img) generation, this open-source UI offers a rich feature set including inpainting, outpainting, attention control, and multiple advanced upscaling options. With a flexible installation process across Windows, Linux, and... -
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DocArray
The data structure for multimodal data
...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. Data science powerhouse: greatly accelerate data scientists’ work on embedding, k-NN matching, querying, visualizing, evaluating via Torch/TensorFlow/ONNX/PaddlePaddle on CPU/GPU. Data in transit: optimized for network communication, ready-to-wire at anytime with fast and compressed serialization in Protobuf, bytes, base64, JSON, CSV, DataFrame. ... -
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Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
...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 network is needed after all. And so research continues. For simpler training, you can directly supply text strings instead of precomputing text encodings. (Although for scaling purposes, you will definitely want to precompute the textual embeddings + mask) -
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Moveable
Draggable, resizable, scalable, rotatable, warpable application
Moveable is draggable, resizable, scalable, rotatable, warpable, pinchable, groupable, and snappable. Draggable refers to the ability to drag and move targets. Resizable indicates whether the target's width and height can be increased or decreased. Scalable indicates whether the target's x and y can be scale of transform. Rotatable indicates whether the target can be rotated. Warpable indicates whether the target can be warped (distorted, bented). Pinchable indicates whether the target can... -
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Big Sleep
A simple command line tool for text to image generation
A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN. Ryan Murdock has done it again, combining OpenAI's CLIP and the generator from a BigGAN! This repository wraps up his work so it is easily accessible to anyone who owns a GPU. You will be able to have the GAN dream-up images using natural language with a one-line command in the terminal. User-made notebook with bug fixes and added features, like google drive integration. -
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Phaser 3 UI Components
Phaser 3 UI Components built by Adobe Animate
Phaser UI Comps is a plugin for Phaser 3 that enables developers to design user interface components using Adobe Animate and export them for use in Phaser games. It streamlines the process of creating interactive UI elements by leveraging JSON and texture atlases generated from Animate. -
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buddidictionary
An English to Sinhala Dictionary with Morphological Processing
Buddidictionary is an English to Sinhala bilingual dictionary embed with English and Sinhala Morphological analysis. the system has been developed as a part of the EnSiMaS Project which is capable to translate English sentence into Sinhala. System has been developed through the MaSMT MUlti agent system development framework -
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Clipper/XBase compatible compiler with initial support other xBase dialects. Multitasking, OOP,SIX/Comix, SQL and ODBC drivers,a C-API for third-party developers, a few wrappers for popular libraries (such as BZIP, GZIP, GD, Crypto, and Fcgi), ....
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11
MatrixTurn
MatixTurn is an AS3 Library used for Flash games optimizations.
...The technique is to transform each vector graphic animation, into cached matrices, for a better computer calculation and a very fast real time rendering. Keep your files low in datasize without manually transform each of your your movie clip in bitmap. All process is done on real time processing with integrated progress bar per-loading system. -
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A framework and Java class for rapid development of quiz apps for Android-smartphones. Preview-clip: http://youtu.be/QmBexUPsqm0 I have currently no resources to push this project further. However, if you're interested feel free to contact me - depending on the feedback I receive I might re-arrange my priorities.
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CLiP is a Command Line Parser written in C. Its flexible structure and easy use make it a quick and fast parser you should absolutely try! Among others, it allows you to define short and long prefixes, the number of arguments for a certain option...
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