3 projects for "annotation" with 2 filters applied:

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  • 1
    Segment Anything

    Segment Anything

    Provides code for running inference with the SegmentAnything Model

    ...The architecture separates a powerful image encoder from a lightweight mask decoder, so the heavy vision work can be computed once and the interactive part stays fast. A bundled automatic mask generator can sweep an image and propose many object masks, which is useful for dataset bootstrapping or bulk annotation. The repository includes ready-to-use weights, Python APIs, and example notebooks demonstrating both interactive and automatic modes. Because SAM was trained with an extremely large and diverse mask dataset, it tends to generalize well to new domains, making it a practical starting point for research and production annotation tools.
    Downloads: 3 This Week
    Last Update:
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  • 2
    SAM 2

    SAM 2

    The repository provides code for running inference with SAM 2

    ...The updated model is optimized for faster inference and lower memory use, enabling real-time interactivity even on larger images or constrained hardware. SAM2 comes with pretrained weights and easy-to-use APIs, enabling developers and researchers to integrate promptable segmentation into annotation tools, vision pipelines, or downstream tasks. The project also includes scripts and notebooks to compare SAM2 against SAM on edge cases, benchmarks showing improvements, and evaluation suites to measure mask quality metrics like IoU and boundary error.
    Downloads: 11 This Week
    Last Update:
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  • 3
    DensePose

    DensePose

    A real-time approach for mapping all human pixels of 2D RGB images

    ...This enables detailed understanding of human shape, motion, and surface appearance directly from images or videos. The repository includes the DensePose network architecture, training code, pretrained models, and dataset tools for annotation and visualization. DensePose is widely used in augmented reality, motion capture, virtual try-on, and visual effects applications because it enables real-time 3D human mapping from 2D inputs. The model architecture builds on Mask R-CNN, using additional regression heads to predict UV coordinates that map image pixels to 3D surfaces.
    Downloads: 26 This Week
    Last Update:
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