Search Results for "python image editor" - Page 3
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Showing 314 open source projects for "python image editor"
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Diffusers
State-of-the-art diffusion models for image and audio generation
Diffusers is the go-to library for state-of-the-art pretrained diffusion models for generating images, audio, and even 3D structures of molecules. Whether you're looking for a simple inference solution or training your own diffusion models, Diffusers is a modular toolbox that supports both. Our library is designed with a focus on usability over performance, simple over easy, and customizability over abstractions. State-of-the-art diffusion pipelines that can be run in inference with just a... -
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Watermark Anything
Official implementation of Watermark Anything with Localized Messages
Watermark Anything (WAM) is an advanced deep learning framework for embedding and detecting localized watermarks in digital images. Developed by Facebook Research, it provides a robust, flexible system that allows users to insert one or multiple watermarks within selected image regions while maintaining visual quality and recoverability. Unlike traditional watermarking methods that rely on uniform embedding, WAM supports spatially localized watermarks, enabling targeted protection of... -
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MMDeploy
OpenMMLab Model Deployment Framework
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN... -
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ChatGPT Telegram Bot
A Telegram bot that integrates with OpenAI's official ChatGPT APIs
A Telegram bot that integrates with OpenAI's official ChatGPT, DALL·E and Whisper APIs to provide answers. Ready to use with minimal configuration required. -
Pest Control Management SoftwareBuilt for the pest control industry, but also works great for Mosquito Control, Bin Cleaning, Window Washing, Solar Panel Cleaning, and other Home Service Businesses in need of an easy-to-use software that helps you simplify routing, scheduling, communications, payment processing, truck tracking, time tracking, and reporting.
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Stable Diffusion Version 2
High-Resolution Image Synthesis with Latent Diffusion Models
Stable Diffusion (the stablediffusion repo by Stability-AI) is an open-source implementation and reference codebase for high-resolution latent diffusion image models that power many text-to-image systems. The repository provides code for training and running Stable Diffusion-style models, instructions for installing dependencies (with notes about performance libraries like xformers), and guidance on hardware/driver requirements for efficient GPU inference and training. It’s organized as a... -
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MESHROOM
3D reconstruction software
Photogrammetry is the science of making measurements from photographs. It infers the geometry of a scene from a set of unordered photographies or videos. Photography is the projection of a 3D scene onto a 2D plane, losing depth information. The goal of photogrammetry is to reverse this process. The dense modeling of the scene is the result yielded by chaining two computer vision-based pipelines, “Structure-from-Motion” (SfM) and “Multi View Stereo” (MVS). Fusion of Multi-bracketing LDR... -
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Milvus Bootcamp
Dealing with all unstructured data, such as reverse image search
Milvus Bootcamp is a collection of tutorials, examples, and best practices for using Milvus, an open-source vector database designed for AI-powered similarity search and retrieval applications. -
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POT
Python Optimal Transport
This open source Python library provides several solvers for optimization problems related to Optimal Transport for signal, image processing and machine learning. -
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YOLOv5
YOLOv5 is the world's most loved vision AI
Introducing Ultralytics YOLOv8, the latest version of the acclaimed real-time object detection and image segmentation model. YOLOv8 is built on cutting-edge advancements in deep learning and computer vision, offering unparalleled performance in terms of speed and accuracy. Its streamlined design makes it suitable for various applications and easily adaptable to different hardware platforms, from edge devices to cloud APIs. Explore the YOLOv8 Docs, a comprehensive resource designed to help... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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SageMaker Training Toolkit
Train machine learning models within Docker containers
Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and... -
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VisualGLM-6B
Chinese and English multimodal conversational language model
VisualGLM-6B is an open-source multimodal conversational language model developed by ZhipuAI that supports both images and text in Chinese and English. It builds on the ChatGLM-6B backbone, with 6.2 billion language parameters, and incorporates a BLIP2-Qformer visual module to connect vision and language. In total, the model has 7.8 billion parameters. Trained on a large bilingual dataset — including 30 million high-quality Chinese image-text pairs from CogView and 300 million English pairs... -
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OpenCLIP
An open source implementation of CLIP
The goal of this repository is to enable training models with contrastive image-text supervision and to investigate their properties such as robustness to distribution shift. Our starting point is an implementation of CLIP that matches the accuracy of the original CLIP models when trained on the same dataset. Specifically, a ResNet-50 model trained with our codebase on OpenAI's 15 million image subset of YFCC achieves 32.7% top-1 accuracy on ImageNet. OpenAI's CLIP model reaches 31.3% when... -
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FramePack
Lets make video diffusion practical
FramePack explores compact representations for sequences of image frames, targeting tasks where many near-duplicate frames carry redundant information. The idea is to “pack” frames by detecting shared structure and storing differences efficiently, which can accelerate training or inference on video-like data. By reducing I/O and memory bandwidth, datasets become lighter to load while models still see the essential temporal variation. The repository demonstrates both packing and unpacking... -
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Upsonic
The most reliable AI agent framework that supports MCP
Upsonic is a reliability-focused AI agent framework designed for real-world applications. It enables the development of trusted agent workflows within organizations by incorporating advanced reliability features, such as verification layers and output evaluation systems. The framework supports the Model Context Protocol (MCP), facilitating integration with various tools and enhancing agent capabilities. -
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Style Aligned
Official code for Style Aligned Image Generation via Shared Attention
StyleAligned is a diffusion-model editing technique and codebase that preserves the visual “style” of an original image while applying new semantic edits driven by text. Instead of fully re-generating an image—and risking changes to lighting, texture, or rendering choices—the method aligns internal features across denoising steps so the target edit inherits the source style. This alignment acts like a constraint on the model’s evolution, steering composition, palette, and brushwork even as... -
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ImageBind
ImageBind One Embedding Space to Bind Them All
ImageBind is a multimodal embedding framework that learns a shared representation space across six modalities—images, text, audio, depth, thermal, and IMU (inertial motion) data—without requiring explicit pairwise training for every modality combination. Instead of aligning each pair independently, ImageBind uses image data as the central binding modality, aligning all other modalities to it so they can interoperate zero-shot. This creates a unified embedding space where representations from... -
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DINOv3
Reference PyTorch implementation and models for DINOv3
DINOv3 is the third-generation iteration of Meta’s self-supervised visual representation learning framework, building upon the ideas from DINO and DINOv2. It continues the paradigm of learning strong image representations without labels using teacher–student distillation, but introduces a simplified and more scalable training recipe that performs well across datasets and architectures. DINOv3 removes the need for complex augmentations or momentum encoders, streamlining the pipeline while... -
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Open-Sora
Open-Sora: Democratizing Efficient Video Production for All
Open-Sora is an open-source initiative aimed at democratizing high-quality video production. It offers a user-friendly platform that simplifies the complexities of video generation, making advanced video techniques accessible to everyone. The project embraces open-source principles, fostering creativity and innovation in content creation. Open-Sora provides tools, models, and resources to create high-quality videos, aiming to lower the entry barrier for video production and support diverse... -
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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... -
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Hunyuan3D 2.0
High-Resolution 3D Assets Generation with Large Scale Diffusion Models
The Hunyuan3D-2 model, developed by Tencent, is designed for generating high-resolution 3D assets using large-scale diffusion models. This model offers advanced capabilities for creating detailed 3D models, including texture enhancements, multi-view shape generation, and rapid inference for real-time applications. It is particularly useful for industries requiring high-quality 3D content, such as gaming, film, and virtual reality. Hunyuan3D-2 supports various enhancements and is available... -
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Elyra
Elyra extends JupyterLab with an AI centric approach
Elyra is a set of AI-centric extensions to JupyterLab Notebooks. The Elyra Getting Started Guide includes more details on these features. A version-specific summary of new features is located on the releases page. -
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Transformers
State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX
...Text, for tasks like text classification, information extraction, question answering, summarization, translation, text generation, in over 100 languages. Images, for tasks like image classification, object detection, and segmentation. Audio, for tasks like speech recognition and audio classification. Transformers provides APIs to quickly download and use those pretrained models on a given text, fine-tune them on your own datasets and then share them with the community on our model hub. At the same time, each python module defining an architecture is fully standalone and can be modified to enable quick research experiments. -
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BackgroundMattingV2
Real-Time High-Resolution Background Matting
Official repository for the paper Real-Time High-Resolution Background Matting. Our model requires capturing an additional background image and produces state-of-the-art matting results at 4K 30fps and HD 60fps on an Nvidia RTX 2080 TI GPU. -
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Nexa SDK
Nexa SDK is a comprehensive toolkit for supporting ONNX and GGML
Nexa SDK is a comprehensive toolkit for supporting ONNX and GGML models. It supports text generation, image generation, vision-language models (VLM), and speech-to-text (ASR), and text-to-speech (TTS) capabilities. Additionally, it offers an OpenAI-compatible API server with JSON schema mode for function calling and streaming support, and a user-friendly Streamlit UI. Users can run Nexa SDK in any device with Python environment, and GPU acceleration is supported, including CUDA, Metal, and ROCm. ... -
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Qwen2.5-Omni
Capable of understanding text, audio, vision, video
Qwen2.5-Omni is an end-to-end multimodal flagship model in the Qwen series by Alibaba Cloud, designed to process multiple modalities (text, images, audio, video) and generate responses both as text and natural speech in streaming real-time. It supports “Thinker-Talker” architecture, and introduces innovations for aligning modalities over time (for example synchronizing video/audio), robust speech generation, and low-VRAM/quantized versions to make usage more accessible. It holds...
