Showing 4 open source projects for "image annotate"

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  • 1
    Computer Vision Annotation Tool (CVAT)

    Computer Vision Annotation Tool (CVAT)

    Interactive video and image annotation tool for computer vision

    Computer Vision Annotation Tool (CVAT) is a free and open source, interactive online tool for annotating videos and images for Computer Vision algorithms. It offers many powerful features, including automatic annotation using deep learning models, interpolation of bounding boxes between key frames, LDAP and more. It is being used by its own professional data annotation team to annotate millions of objects with different properties. The UX and UI were also specially developed by the team...
    Downloads: 20 This Week
    Last Update:
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  • 2
    supervision

    supervision

    We write your reusable computer vision tools

    We write your reusable computer vision tools. Whether you need to load your dataset from your hard drive, draw detections on an image or video, or count how many detections are in a zone. You can count on us.
    Downloads: 1 This Week
    Last Update:
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  • 3
    COCO Annotator

    COCO Annotator

    Web-based image segmentation tool for object detection & localization

    ... and customizable interface and provides many tools for creating accurate datasets. Several annotation tools are currently available, with most applications as a desktop installation. Once installed, users can manually define regions in an image and creating a textual description. Generally, objects can be marked by a bounding box, either directly, through a masking tool, or by marking points to define the containing area. COCO Annotator allows users to annotate images using free-form curves.
    Downloads: 3 This Week
    Last Update:
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  • 4
    LabelImg

    LabelImg

    Graphical image annotation tool and label object bounding boxes

    LabelImg is a graphical image annotation tool. It is written in Python and uses Qt for its graphical interface. Annotations are saved as XML files in PASCAL VOC format, the format used by ImageNet. Besides, it also supports YOLO and CreateML formats. Linux/Ubuntu/Mac requires at least Python 2.6 and has been tested with PyQt 4.8. However, Python 3 or above and PyQt5 are strongly recommended. Virtualenv can avoid a lot of the QT / Python version issues. Build and launch using the instructions...
    Downloads: 119 This Week
    Last Update:
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