5 projects for "chart" with 2 filters applied:

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  • 1
    DeepSeek-OCR

    DeepSeek-OCR

    Contexts Optical Compression

    DeepSeek-OCR is an open-source optical character recognition solution built as part of the broader DeepSeek AI vision-language ecosystem. It is designed to extract text from images, PDFs, and scanned documents, and integrates with multimodal capabilities that understand layout, context, and visual elements beyond raw character recognition. The system treats OCR not simply as “read the text” but as “understand what the text is doing in the image”—for example distinguishing captions from body...
    Downloads: 7 This Week
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  • 2
    AutoViz

    AutoViz

    Automatically Visualize any dataset, any size

    AutoViz is a Python data visualization library designed to automate exploratory data analysis by generating multiple visualizations with minimal code. The primary goal of the project is to help data scientists and analysts quickly understand patterns, relationships, and anomalies within datasets without manually writing complex plotting code. With a single command, the library can automatically generate dozens of charts and graphs that reveal insights into the structure and quality of the...
    Downloads: 0 This Week
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  • 3
    ML Ferret

    ML Ferret

    Refer and Ground Anything Anywhere at Any Granularity

    ...The repo presents the vision-language pipeline, model assets, and paper resources that show how Ferret answers questions, follows instructions, and returns grounded outputs rather than just text. In practice, this enables tasks like “find that small red icon next to the chart and describe it” where both the linguistic reference and the visual region are ambiguous without fine spatial reasoning.
    Downloads: 0 This Week
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  • 4
    Simple neural network(s) simulator. Moved as plugin under EDU Sand Box (https://sourceforge.net/projects/esbox/) project.
    Downloads: 31 This Week
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  • 5
    Qwen2.5-VL-3B-Instruct

    Qwen2.5-VL-3B-Instruct

    Qwen2.5-VL-3B-Instruct: Multimodal model for chat, vision & video

    Qwen2.5-VL-3B-Instruct is a 3.75 billion parameter multimodal model by Qwen, designed to handle complex vision-language tasks in both image and video formats. As part of the Qwen2.5 series, it supports image-text-to-text generation with capabilities like chart reading, object localization, and structured data extraction. The model can serve as an intelligent visual agent capable of interacting with digital interfaces and understanding long-form videos by dynamically sampling resolution and frame rate. It uses a SwiGLU and RMSNorm-enhanced ViT architecture and introduces mRoPE updates for robust temporal and spatial understanding. ...
    Downloads: 0 This Week
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