Search Results for "morphological image processing" - Page 25

Showing 618 open source projects for "morphological image processing"

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  • 1
    Prolog Image Processing is a (initially) MacOS based extension to OpenProlog which allows to use image processing function in the context of Prolog.
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  • 2
    An image processing environment, based in Java, and developed on the concept of filters applied to an input. Maybe it will work out, maybe it won't. But it's better then wasting space on SourceForge for an old game...
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  • 3
    C++ library that implements basic data structures and algorithms for computer vision and image processing applications
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  • 4
    Hylafax Job Control Langauge (HJCL) is a batch processing perl script front end for Hylafax using PERL MAGICK and IMAGE MAGICK. Scans a directory for fax jobs and submits them to Hylafax.
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  • 5
    A numerical library designed for n-dimensional image-processing written in Java.
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  • 6
    A set of Matlab toolboxes to perform signal and image processing.
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  • 7
    Various projects from Digital Image Processing and Computer Graphics club of Warsaw University of Technology.
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  • 8
    The Data Fusion Peer is a multitier computer vision internet application. The system provides image processing, motion tracking, and visualization information. Application will convert data into 3-Deminsional and other digital environments.
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  • 9

    geoscipy

    Python-accessible toolkit for Geoscience & Remote Sensing Applications

    ...There is also a Python API that provides a procedural as well as an object-oriented interface to these functions. A Python GUI for interacting with such datasets is also part of the project. While there are other open-source GIS, and image-processing packages available, this one is designed to be comprehensive, work on 3 major platforms, user-extensible, fast, and able to handle huge datasets. Click the Blog tab for more info.
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  • 10
    SeeHawk is a cross-platform, cross-device video/image capturing, viewing, and editing application.
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  • 11

    KinectStreamer

    Streams data from 3D cameras over a network.

    This is an application that streams data from the Microsoft Kinect or cameras like it over a network. The program is Intended to be used in robotics applications where the controller cannot use such cameras directly due to hardware/software limitations--such as lacking usb ports or appropriate drivers--or in situations where the camera is not in close proximity to the device that needs to access it. Given that the controller can accept data from over the network, another embedded controller...
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  • 12
    GLM-5.3-Flash

    GLM-5.3-Flash

    Efficient 320B multimodal MoE model for coding and autonomous agents

    GLM-5.3-Flash is Z.ai’s natively multimodal model designed for efficient coding, agentic engineering, reasoning, and long-context workloads. It uses a sparse architecture with 320B total parameters and only 18B active parameters, targeting high capability with substantially lower inference costs. The model introduces a hybrid architecture combining sparse and linear attention to reduce long-context serving costs while retaining precise understanding across large inputs. It also uses...
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  • 13
    Gemma 4

    Gemma 4

    Google’s flagship dense multimodal model for coding and reasoning

    Gemma 4 is Google DeepMind’s flagship dense open-weight multimodal model, designed for high-end reasoning, coding, agentic workflows, and multimodal understanding. The model contains approximately 30.7B parameters and supports text and image inputs with text generation output, while also processing video as image-frame sequences. Built as the most capable model in the Gemma 4 family, it combines strong reasoning performance with a large 256K-token context window and configurable thinking modes. Gemma 4 31B supports native function calling, structured outputs, and more than 140 languages, making it suitable for enterprise assistants, coding agents, document analysis, and multilingual applications. ...
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  • 14
    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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  • 15
    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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  • 16
    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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  • 17
    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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  • 18
    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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