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achaiah avatar

achaiah/pywick

0
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Pywick

High-level batteries-included neural network training library for Pytorch

Features

  • Computer Vision - Segmentation and training framework.

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  • Developer Tools - Batteries-included training library.
  • Segmentation - Listed in the “Segmentation” section of the The Incredible Pytorch awesome list.
  • 400 stars·39 forks·Python·12 views

    Star history

    Star history chart for achaiah/pywickStar history chart for achaiah/pywick

    How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

    Projects sharing features with Pywick

    These projects share indexed features with Pywick. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
    • bodokaiser/piwisebodokaiser avatar

      bodokaiser/piwise

      387View on GitHub↗

      Pixel-wise segmentation on the VOC2012dataset dataset using pytorchpytorch.

      Python
      View on GitHub↗387
    • catalyst-team/segmentationcatalyst-team avatar

      catalyst-team/segmentation

      28View on GitHub↗

      Catalyst.Segmentation

      Python
      View on GitHub↗28
    • albumentations-team/albumentationsalbumentations-team avatar

      albumentations-team/albumentations

      15,308View on GitHub↗

      Albumentations is a computer vision image augmentation library designed to increase training data diversity for deep learning models. It provides a toolset for applying geometric and color transformations to images and annotations, including a specialized collection of 3D operations for volumetric data used in medical and scientific imaging. The library functions as an image mask and bounding box transformer, automatically updating masks, bounding boxes, and keypoints when images undergo geometric changes. This ensures that spatial alterations remain synchronized across images and their assoc

      Python
      View on GitHub↗15,308
    • facebookresearch/detectron2facebookresearch avatar

      facebookresearch/detectron2

      34,548View on GitHub↗

      Detectron2 is a PyTorch computer vision framework and visual recognition platform designed for training and deploying models for object detection, image segmentation, and visual recognition. It provides a research-oriented environment for training complex vision models with multi-GPU acceleration. The project includes a specialized object detection library for identifying and locating multiple objects via bounding boxes, as well as an image segmentation toolkit for creating pixel-level masks through instance, semantic, and panoptic segmentation. Additionally, it features a human pose estimati

      Python
      View on GitHub↗34,548
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    Frequently asked questions

    What does achaiah/pywick do?

    High-level batteries-included neural network training library for Pytorch

    What are the main features of achaiah/pywick?

    The main features of achaiah/pywick are: Computer Vision, Developer Tools, Segmentation.

    Which projects share features with achaiah/pywick?

    Projects with overlapping indexed features include: catalyst-team/segmentation — Catalyst.Segmentation. jianqiangwan/super-bpd — Super-BPD: Super Boundary-to-Pixel Direction for Fast Image Segmentation (CVPR 2020). albumentations-team/albumentations — Albumentations is a computer vision image augmentation library designed to increase training data diversity for deep… bodokaiser/piwise — Pixel-wise segmentation on the [VOC2012][dataset] dataset using [pytorch][pytorch]. facebookresearch/detectron2 — Detectron2 is a PyTorch computer vision framework and visual recognition platform designed for training and deploying… lukemelas/efficientnet-pytorch — This is a PyTorch implementation of EfficientNet convolutional neural networks. It serves as a computer vision model…