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cnn-image-classification-of-flowers

Trained on several thousand flower images.

https://github.com/bhatiadivtej/cnn-image-classification-of-flowers

Science Score: 44.0%

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    Found CITATION.cff file
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    Low similarity (16.5%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Trained on several thousand flower images.

Basic Info
  • Host: GitHub
  • Owner: BhatiaDivtej
  • License: apache-2.0
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 4.06 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 2 years ago · Last pushed over 2 years ago
Metadata Files
Readme License Citation

README.md

Build Status Documentation Status codecov license

Introduction

English | 简体中文

MMClassification is an open source image classification toolbox based on PyTorch. It is a part of the OpenMMLab project.

Documentation: https://mmclassification.readthedocs.io/en/latest/

demo

Major features

  • Various backbones and pretrained models
  • Bag of training tricks
  • Large-scale training configs
  • High efficiency and extensibility

License

This project is released under the Apache 2.0 license.

Changelog

v0.15.0 was released in 31/8/2021. Please refer to changelog.md for details and release history.

Benchmark and model zoo

Results and models are available in the model zoo.

Supported backbones:

  • [x] ResNet
  • [x] ResNeXt
  • [x] SE-ResNet
  • [x] SE-ResNeXt
  • [x] RegNet
  • [x] ShuffleNetV1
  • [x] ShuffleNetV2
  • [x] MobileNetV2
  • [x] MobileNetV3
  • [x] Swin-Transformer

Installation

Please refer to install.md for installation and dataset preparation.

Getting Started

Please see getting_started.md for the basic usage of MMClassification. There are also tutorials for finetuning models, adding new dataset, designing data pipeline, and adding new modules.

Citation

If you find this project useful in your research, please consider cite:

BibTeX @misc{2020mmclassification, title={OpenMMLab's Image Classification Toolbox and Benchmark}, author={MMClassification Contributors}, howpublished = {\url{https://github.com/open-mmlab/mmclassification}}, year={2020} }

Contributing

We appreciate all contributions to improve MMClassification. Please refer to CONTRUBUTING.md for the contributing guideline.

Acknowledgement

MMClassification is an open source project that is contributed by researchers and engineers from various colleges and companies. We appreciate all the contributors who implement their methods or add new features, as well as users who give valuable feedbacks. We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new classifiers.

Projects in OpenMMLab

  • MMCV: OpenMMLab foundational library for computer vision.
  • MIM: MIM Installs OpenMMLab Packages.
  • MMClassification: OpenMMLab image classification toolbox and benchmark.
  • MMDetection: OpenMMLab detection toolbox and benchmark.
  • MMDetection3D: OpenMMLab's next-generation platform for general 3D object detection.
  • MMSegmentation: OpenMMLab semantic segmentation toolbox and benchmark.
  • MMAction2: OpenMMLab's next-generation action understanding toolbox and benchmark.
  • MMTracking: OpenMMLab video perception toolbox and benchmark.
  • MMPose: OpenMMLab pose estimation toolbox and benchmark.
  • MMEditing: OpenMMLab image and video editing toolbox.
  • MMOCR: OpenMMLab toolbox for text detection, recognition and understanding.
  • MMGeneration: OpenMMlab toolkit for generative models.

Owner

  • Name: Divtej Singh Bhatia
  • Login: BhatiaDivtej
  • Kind: user
  • Location: Delhi -> Hong Kong

I love technology, business and their inter-connection which creates an entire new dimension of possibilities.

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
title: "OpenMMLab's Image Classification Toolbox and Benchmark"
authors:
  - name: "MMClassification Contributors"
version: 0.15.0
date-released: 2020-07-09
repository-code: "https://github.com/open-mmlab/mmclassification"
license: Apache-2.0

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Dependencies

docker/Dockerfile docker
  • pytorch/pytorch ${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel build
docker/serve/Dockerfile docker
  • pytorch/pytorch ${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel build
mmcls.egg-info/requires.txt pypi
  • matplotlib *
  • numpy *
requirements/docs.txt pypi
  • docutils ==0.16.0
  • recommonmark *
  • sphinx ==4.0.2
  • sphinx_markdown_tables *
  • sphinx_rtd_theme ==0.5.2
requirements/mminstall.txt pypi
  • mmcv-full >=1.3.8,<=1.5.0
requirements/optional.txt pypi
  • albumentations >=0.3.2
requirements/readthedocs.txt pypi
  • mmcv >=1.3.8
  • torch *
  • torchvision *
requirements/runtime.txt pypi
  • matplotlib *
  • numpy *
requirements/tests.txt pypi
  • codecov * test
  • flake8 * test
  • interrogate * test
  • isort ==4.3.21 test
  • mmdet * test
  • pytest * test
  • xdoctest >=0.10.0 test
  • yapf * test
requirements.txt pypi
setup.py pypi