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A deep-learning package contains a set of well-organized deep-neural networks&tools.

Project description

pip install zhenglin

@ Author: zhenglin @version: 3.0.1

This package contains some off-the-shelves deep-learning networks implemented with .

use

pip install zhenglin

to install this package.

Major Updates

  • Aug 7 2025: Version: 3.0.1. Add patchify, vr and cv function updates.
  • May 31 2025: Version: 3.0.0. Introduce FileSystem class under filesystem, use a pre-defined 1 or 2-layer folder structure to rapidly manage batch image or video datasets.
  • Apr 30 2025: Version: 2.1. Add a new class wrapper vd class under supercv, supports video io now.
  • Apr 18 2025: Version: 2.0. Add init version of supercv(cv) class, a universal wrapper for cv2, PIL.Image and Torch.tensor.
  • Nov 13 2024: Version: 1.21. Package overhaul. Add huggingface accelerate, pytorch-lightning, and pytorch-ddp support.
  • Oct 26 2023: Version: 1.20.19 Add TransUNet and SwinUNet
  • Aug 13 2023: Version: 1.18.15 Add basic quantization support.

Introduction

zhenglin package was motivated by eriklindernoren and his repo which provides many grab-and-run implementation of DL variants. It is the level ground for zhenglin's deep learning projects.

Specifically, this package provides

  • universal structure-template:
    • zhenglin.accelerate.train
    • zhenglin.lightning.train
    • zhenglin.pytorch.train
  • loss functions and metrics
    • zhenglin.utils.loss
    • zhenglin.utils.metrics
  • utils
    • zhenglin.utils.utils
  • 20 modular deep-learning networks
    • zhenglin.networks.*

Networks(Alphabetically):

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