Showing 436 open source projects for "image text input"

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  • 1
    Qwen-Image

    Qwen-Image

    Qwen-Image is a powerful image generation foundation model

    Qwen-Image is a powerful 20-billion parameter foundation model designed for advanced image generation and precise editing, with a particular strength in complex text rendering across diverse languages, especially Chinese. Built on the MMDiT architecture, it achieves remarkable fidelity in integrating text seamlessly into images while preserving typographic details and layout coherence.
    Downloads: 19 This Week
    Last Update:
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  • 2
    LongCat-Image

    LongCat-Image

    Foundation model for image generation

    ...The model excels at both text-to-image generation and instruction-guided image editing, offering users versatile capabilities for creative and practical tasks—whether generating art, mockups, or adjusting existing visuals with fine control.
    Downloads: 5 This Week
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  • 3
    OCRmyPDF

    OCRmyPDF

    OCRmyPDF adds an OCR text layer to scanned PDF files

    OCRmyPDF adds an optical character recognition (OCR) text layer to scanned PDF files, allowing them to be searched. PDF is the best format for storing and exchanging scanned documents. Unfortunately, PDFs can be difficult to modify. OCRmyPDF makes it easy to apply image processing and OCR (recognized, searchable text) to existing PDFs.
    Downloads: 107 This Week
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  • 4
    Boogu-Image-0.1

    Boogu-Image-0.1

    Apache-2.0 open-source image generation and editing model family

    Boogu-Image is an open-source image generation and editing model family focused on unified multimodal understanding and generation. It includes Base, Turbo, Edit, and Edit-Turbo variants for different speed and quality needs. The project supports text-to-image generation, image-to-image editing, fast distilled inference, and Chinese-English text rendering.
    Downloads: 0 This Week
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  • 5
    Qwen-Image-2.1

    Qwen-Image-2.1

    Qwen's most powerful open-source image generation model

    Qwen-Image-2.1 is an open-source 7B-parameter image generation and editing model from the Qwen family. It unifies text-to-image creation and image editing within the same architecture. The model can natively generate transparent RGBA images, edit transparent layers, and extract subjects from photographs. Image editing supports up to 10 reference images for multi-subject composition and identity preservation.
    Downloads: 21 This Week
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  • 6
    FireRed-Image-Edit

    FireRed-Image-Edit

    General-purpose image editing model that delivers high-fidelity

    FireRed-Image-Edit is an open-source general-purpose image editing model and toolset designed to deliver high-fidelity, visually coherent edits across a wide range of editing tasks, from simple object modifications to complex enhancements like restoration and style preservation. It is built on a flexible text-to-image foundation model that has been extended with training paradigms including pretraining, supervised fine-tuning, and reinforcement learning to imbue the system with strong instruction following and editing consistency. ...
    Downloads: 2 This Week
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  • 7
    MiniMax H3

    MiniMax H3

    MiniMax H3 is a general-purpose, omni-modal generative system

    MiniMax H3 is an omni-modal generative system for creating synchronized video and native stereo audio from complex multimodal instructions. It can understand combinations of text, images, video, and audio as generation context. Outputs range from four to fifteen seconds at 24 frames per second, with multiple aspect ratios and resolutions up to 2K. H3-Base supports text-to-video, first-frame, last-frame, and first-and-last-frame generation. Ref2VA accepts multiple reference images, videos,...
    Downloads: 131 This Week
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  • 8
    ComfyUI-HunyuanVideoWrapper

    ComfyUI-HunyuanVideoWrapper

    ComfyUI wrapper nodes for HunyuanVideo

    The ComfyUI-HunyuanVideoWrapper project is a ComfyUI extension that integrates Hunyuan-based multimodal video generation models into node-based workflows. It allows users to generate or manipulate video content by combining text prompts with one or more input images, enabling flexible conditioning of outputs. The system introduces specialized nodes such as text-image encoders that allow multiple image inputs to be referenced directly within prompts. This makes it possible to guide generation using both visual and textual context simultaneously. The wrapper is designed to fit seamlessly into ComfyUI pipelines, enabling chaining with other nodes for advanced workflows. ...
    Downloads: 1 This Week
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  • 9
    FLUX.2

    FLUX.2

    Official inference repo for FLUX.2 models

    FLUX.2 is a state-of-the-art open-weight image generation and editing model released by Black Forest Labs aimed at bridging the gap between research-grade capabilities and production-ready workflows. The model offers both text-to-image generation and powerful image editing, including editing of multiple reference images, with fidelity, consistency, and realism that push the limits of what open-source generative models have achieved.
    Downloads: 34 This Week
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  • 10
    DeepSeek VL2

    DeepSeek VL2

    Mixture-of-Experts Vision-Language Models for Advanced Multimodal

    DeepSeek-VL2 is DeepSeek’s vision + language multimodal model—essentially the next-gen successor to their first vision-language models. It combines image and text inputs into a unified embedding / reasoning space so that you can query with text and image jointly (e.g. “What’s going on in this scene?” or “Generate a caption appropriate to context”). The model supports both image understanding (vision tasks) and multimodal reasoning, and is likely used as a component in agent systems to process visual inputs as context for downstream tasks. ...
    Downloads: 2 This Week
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  • 11
    Mozc

    Mozc

    Mozc - a Japanese Input Method Editor designed for multi-platform

    Mozc is an open source Japanese Input Method Editor (IME) developed by Google, designed to provide Japanese text input across multiple operating systems including Android, macOS, Windows, GNU/Linux, and Chromium OS. The project originated as a subset of Google Japanese Input, released publicly under the BSD 3-Clause license for community use and development. Mozc offers core IME functionality such as text conversion, prediction, and dictionary-based input, enabling users to efficiently type and edit Japanese text. ...
    Downloads: 11 This Week
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  • 12
    HunyuanCustom

    HunyuanCustom

    Multimodal-Driven Architecture for Customized Video Generation

    HunyuanCustom is a multimodal video customization framework by Tencent Hunyuan, aimed at generating customized videos featuring particular subjects (people, characters) under flexible conditions, while maintaining subject/identity consistency. It supports conditioning via image, audio, video, and text, and can perform subject replacement in videos, generate avatars speaking given audio, or combine multiple subject images. The architecture builds on HunyuanVideo, with added modules for identity reinforcement and modality-specific condition injection. Text-image fusion module based on LLaVA for improved multimodal understanding. ...
    Downloads: 0 This Week
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  • 13
    Hunyuan3D 2.0

    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...
    Downloads: 49 This Week
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  • 14
    Qwen3-Omni

    Qwen3-Omni

    Qwen3-omni is a natively end-to-end, omni-modal LLM

    Qwen3-Omni is a natively end-to-end multilingual omni-modal foundation model that processes text, images, audio, and video and delivers real-time streaming responses in text and natural speech. It uses a Thinker-Talker architecture with a Mixture-of-Experts (MoE) design, early text-first pretraining, and mixed multimodal training to support strong performance across all modalities without sacrificing text or image quality. The model supports 119 text languages, 19 speech input languages, and 10 speech output languages. ...
    Downloads: 1 This Week
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  • 15
    Qwen2.5-Omni

    Qwen2.5-Omni

    Capable of understanding text, audio, vision, video

    ...It holds state-of-the-art performance in many multimodal benchmarks, particularly spoken language understanding, audio reasoning, image/video understanding, etc. Very strong benchmark performance across modalities (audio understanding, speech recognition, image/video reasoning) and often outperforming or matching single-modality models at a similar scale. Real-time streaming responses, including natural speech synthesis (text-to-speech) and chunked inputs for low latency interaction.
    Downloads: 1 This Week
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  • 16
    Pixal3D

    Pixal3D

    Pixel-Aligned 3D Generation from Images

    Pixal3D is a TencentARC research project for generating high-fidelity 3D assets from a single input image. It addresses a key weakness in image-to-3D generation: many models produce plausible 3D shapes but fail to preserve pixel-level faithfulness to the original image. Pixal3D improves this by explicitly lifting image features into 3D through back-projection, creating clearer correspondences between the input pixels and the generated asset. ...
    Downloads: 6 This Week
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  • 17
    Qwen-Image-Layered

    Qwen-Image-Layered

    Qwen-Image-Layered: Layered Decomposition for Inherent Editablity

    ...By combining text and structured image representations, it aims to facilitate tasks where both descriptive and structural understanding are important, such as detailed image QA, interactive image editing via prompt layers, and image-conditioned generation with structural control. The layered approach supports training signals that help the model learn how visual elements relate to each other and to textual context, rather than simply learning global image embeddings.
    Downloads: 0 This Week
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  • 18
    CLIP

    CLIP

    CLIP, Predict the most relevant text snippet given an image

    CLIP (Contrastive Language-Image Pretraining) is a neural model that links images and text in a shared embedding space, allowing zero-shot image classification, similarity search, and multimodal alignment. It was trained on large sets of (image, caption) pairs using a contrastive objective: images and their matching text are pulled together in embedding space, while mismatches are pushed apart.
    Downloads: 2 This Week
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  • 19
    FLUX.1

    FLUX.1

    Official inference repo for FLUX.1 models

    FLUX.1 repository contains inference code and tooling for the FLUX.1 text-to-image diffusion models, enabling developers and researchers to generate and edit images from natural-language prompts using open-weight versions of the model on their own hardware or within custom applications. The project is part of a larger family of FLUX models developed by Black Forest Labs, designed to produce high-quality, detailed visuals from text descriptions with competitive prompt adherence and artistic fidelity. ...
    Downloads: 59 This Week
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  • 20
    HunyuanImage-3.0

    HunyuanImage-3.0

    A Powerful Native Multimodal Model for Image Generation

    HunyuanImage-3.0 is a powerful, native multimodal text-to-image generation model released by Tencent’s Hunyuan team. It unifies multimodal understanding and generation in a single autoregressive framework, combining text and image modalities seamlessly rather than relying on separate image-only diffusion components. It uses a Mixture-of-Experts (MoE) architecture with many expert subnetworks to scale efficiently, deploying only a subset of experts per token, which allows large parameter counts without linear inference cost explosion. ...
    Downloads: 2 This Week
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  • 21
    Ideogram 4

    Ideogram 4

    Open image model at the forefront of design

    Ideogram 4 is an open-weight text-to-image model focused on high-quality visual generation, design control, and accurate text rendering inside images. It is built for users who need more than generic image generation, especially when layout, typography, composition, color, and language understanding matter. The project introduces a structured JSON prompting workflow that gives creators more explicit control over scene details and visual constraints.
    Downloads: 0 This Week
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  • 22
    Label Studio

    Label Studio

    Label Studio is a multi-type data labeling and annotation tool

    The most flexible data annotation tool. Quickly installable. Build custom UIs or use pre-built labeling templates. Detect objects on image, bboxes, polygons, circular, and keypoints supported. Partition image into multiple segments. Use ML models to pre-label and optimize the process. Label Studio is an open-source data labeling tool. It lets you label data types like audio, text, images, videos, and time series with a simple and straightforward UI and export to various model formats. ...
    Downloads: 41 This Week
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  • 23
    VoxCPM2

    VoxCPM2

    Tokenizer-Free TTS for Multilingual Speech Generation

    VoxCPM2 is an advanced open-source text-to-speech system that redefines speech synthesis by eliminating traditional tokenization and instead generating continuous speech representations through a diffusion-based autoregressive architecture. Built on top of the MiniCPM model family, it enables highly natural, expressive, and context-aware speech generation that adapts tone, emotion, and pacing directly from input text.
    Downloads: 11 This Week
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  • 24
    Django MarkdownX

    Django MarkdownX

    Comprehensive Markdown plugin built for Django

    Django MarkdownX is a comprehensive Markdown plugin built for Django, the renowned high-level Python web framework, with flexibility, extensibility, and ease-of-use at its core.
    Downloads: 1 This Week
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  • 25
    MiniMind-O

    MiniMind-O

    A 0.1B Omni model trained from scratch

    MiniMind-O is an educational open-source project for building a small end-to-end Omni model from scratch. It extends the MiniMind family by exploring a model that can handle text, audio, and image inputs while producing text and streaming speech outputs. The project is designed to make multimodal AI training more accessible by keeping the model size small enough for ordinary personal hardware. It includes both mini and full training data paths, allowing learners to run a complete workflow quickly or reproduce the released model setup more closely. ...
    Downloads: 0 This Week
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