https://github.com/rahulguptagzb09/video-object-detection-using-ssd

Video Object Detection Using SSD
https://github.com/rahulguptagzb09/video-object-detection-using-ssd

deep-learning object-detection opencv ssd video-processing

Last synced: about 2 hours ago
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Video Object Detection Using SSD

• Host: GitHub
• URL: https://github.com/rahulguptagzb09/video-object-detection-using-ssd
• Owner: rahulguptagzb09
• License: gpl-3.0
• Created: 2019-05-02T16:23:13.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2019-05-02T16:28:12.000Z (over 5 years ago)
• Last Synced: 2024-10-18T19:38:50.047Z (about 1 month ago)
• Topics: deep-learning, object-detection, opencv, ssd, video-processing
• Language: Python
• Size: 27.3 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Video-Object-Detection-Using-SSD

Video Object Detection Using SSD

"""Single Shot Multibox Architecture

    The network is composed of a base VGG network followed by the

    added multibox conv layers.  Each multibox layer branches into

        1) conv2d for class conf scores

        2) conv2d for localization predictions

        3) associated priorbox layer to produce default bounding

           boxes specific to the layer's feature map size.

    See: https://arxiv.org/pdf/1512.02325.pdf for more details.


    Args:

        phase: (string) Can be "test" or "train"

        base: VGG16 layers for input, size of either 300 or 500

        extras: extra layers that feed to multibox loc and conf layers

        head: "multibox head" consists of loc and conf conv layers

    """