Search Results for "image processing framework" - Page 62

Showing 1534 open source projects for "image processing framework"

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  • 1
    Ministral 3 3B Base 2512

    Ministral 3 3B Base 2512

    Small 3B-base multimodal model ideal for custom AI on edge hardware

    ...It supports dozens of languages, making it practical for multilingual, global, or distributed environments. With a large 256k token context window, it can handle long documents, extended inputs, or multi-step processing workflows even at its small size.
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  • 2
    Nex-N2-Pro

    Nex-N2-Pro

    Large agentic model for coding, tools, research, and execution

    ...It supports image-text-to-text workflows, explicit reasoning traces, robust function calling, and deployment through Transformers, vLLM, SGLang, Docker, and quantized local apps. Nex-N2-Pro performs strongly across agentic, coding, search, and reasoning benchmarks, including Terminal-Bench, SWE-Bench Pro, BrowseComp, Toolathlon, WideSearch, GPQA Diamond, and GDPval.
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  • 3
    Reputation-Sentinel-OS-v3

    Reputation-Sentinel-OS-v3

    Autonomous n8n framework for real-time brand protection & AI analysis.

    ...Deep AI Analysis: Surgical sentiment detection (sarcasm, threats, urgency) via local or cloud AI models. Incident Response: Automated rule-based workflows to mitigate damage instantly. Enterprise Power: Optimized for high-load processing without monthly fees. The ultimate self-hosted operating system for PR agencies and security-focused enterprises. Buy once, own forever.
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  • 4
    Inkling-Small

    Inkling-Small

    Efficient multimodal MoE model for coding, tools, and reasoning

    Inkling-Small is an open-weight general-purpose multimodal model from Thinking Machines Lab, designed for agentic systems, coding assistants, chatbots, retrieval workflows, and natural-language applications. It accepts text, images, and audio as input and produces text output, with multilingual and multi-programming-language capabilities. The model uses a sparse Mixture-of-Experts architecture with 276B total parameters and 12B active per token, enabling strong performance with lower...
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    MiMo-V2.5

    MiMo-V2.5

    Omnimodal AI model for agents, coding, and long-context tasks

    MiMo-V2.5 is a native omnimodal large language model developed by Xiaomi, designed for advanced agentic workflows, multimodal reasoning, and long-context processing. Built on a Mixture-of-Experts architecture with approximately 309B total parameters and around 15B activated per inference, it balances high capability with efficient execution. The model natively processes text, images, video, and audio within a unified system, enabling cross-modal understanding and complex task execution in a...
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  • 6
    Ministral 3 8B Instruct 2512

    Ministral 3 8B Instruct 2512

    Compact 8B multimodal instruct model optimized for edge deployment

    Ministral 3 8B Instruct 2512 is a balanced, efficient model in the Ministral 3 family, offering strong multimodal capabilities within a compact footprint. It combines an 8.4B-parameter language model with a 0.4B vision encoder, enabling both text reasoning and image understanding. This FP8 instruct-fine-tuned variant is optimized for chat, instruction following, and structured outputs, making it ideal for daily assistant tasks and lightweight agentic workflows. Designed for edge deployment,...
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  • 7
    Ministral 3 14B Instruct 2512

    Ministral 3 14B Instruct 2512

    Efficient 14B multimodal instruct model with edge deployment and FP8

    Ministral 3 14B Instruct 2512 is the largest model in the Ministral 3 family, delivering frontier performance comparable to much larger systems while remaining optimized for edge-level deployment. It combines a 13.5B-parameter language model with a 0.4B-parameter vision encoder, enabling strong multimodal understanding in both text and image tasks. This FP8 instruct-tuned variant is designed specifically for chat, instruction following, and agentic workflows with robust system-prompt...
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  • 8
    Monk Computer Vision

    Monk Computer Vision

    A low code unified framework for computer vision and deep learning

    Monk is an open source low code programming environment to reduce the cognitive load faced by entry level programmers while catering to the needs of Expert Deep Learning engineers. There are three libraries in this opensource set. - Monk Classiciation- https://monkai.org. A Unified wrapper over major deep learning frameworks. Our core focus area is at the intersection of Computer Vision and Deep Learning algorithms. - Monk Object Detection -...
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  • 9
    Fraunhofer SimWebApp
    Multi-user online service implementation for web-based factory modeling. Rich user interface and scalable backend system to build online simulation services on or do other processing of factory data. Demo at https://fabriksimulation.ipa.fraunhofer.de
    Downloads: 0 This Week
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