ChainerCV is a collection of tools to train and run neural networks for computer vision tasks using Chainer. In ChainerCV, we define the object detection task as a problem of, given an image, bounding box-based localization and categorization of objects. Bounding boxes in an image are represented as a two-dimensional array of shape (R,4), where R is the number of bounding boxes and the second axis corresponds to the coordinates of bounding boxes. ChainerCV supports dataset loaders, which can be used to easily index examples with list-like interfaces. Dataset classes whose names end with BboxDataset contain annotations of where objects locate in an image and which categories they are assigned to. These datasets can be indexed to return a tuple of an image, bounding boxes and labels. ChainerCV provides several network implementations that carry out object detection.

Features

  • You can install ChainerCV using pip
  • Training script for various detection models
  • Bounding boxes in ChainerCV
  • ChainerCV supports dataset loaders
  • A mapping between an integer label and a category differs between datasets
  • ChainerCV provides several network implementations that carry out object detection

Project Samples

Project Activity

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License

MIT License

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Additional Project Details

Programming Language

Python

Related Categories

Python Machine Learning Software, Python Computer Vision Libraries, Python Object Detection Models, Python Deep Learning Frameworks

Registered

2022-08-15