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توضیحات

ویژگی	مقدار
سیستم عامل	-
نام فایل	deepclustering-0.0.3
نام	deepclustering
نسخه کتابخانه	0.0.3
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	Jizong Peng
ایمیل نویسنده	jizong.peng.1@etsmtl.net
آدرس صفحه اصلی	https://github.com/jizongFox/deep-clustering-toolbox
آدرس اینترنتی	https://pypi.org/project/deepclustering/
مجوز	MIT

# deep-clustering-toolbox #### PyTorch Vision toolbox not only for deep-clustering ### Introduction I still use this repo for research propose. I update some modules frequently to make the framework flexible enough. This repo contains the base code for a deep learning framework using `PyTorch`, to benchmark algorithms for various dataset. The current version supports `MNIST`, `CIFAR10`, `SVHN` and `STL-10` for semisupervised and unsupervised learning. `ACDC`, `Promise12`, `WMH` and so on are supported as segmentation counterpart. #### Features: >- Powerful cmd parser using `yaml` module, providing flexible input formats without predefined argparser. >- Automatic checkpoint management adapting to various settings >- Automatic meter recording and experimental status plotting using matplotlib and threads >- Various build-in loss functions and help tricks and assert statements frequently used in PyTorch Framework, such as `disable_tracking_bn`, `ema`, `vat`, etc. >- Various post-processing tools such as Viewer for Medical image segmentations, multislice_viwers for 3D dataset real-time debug and report script for experimental summaries. >- Extendable modules for rapid development. #### Several projects are benefited from this scalable framework, builing top on this, including: + DeepClustering implemented for >- `Invariant Information Clustering for Unsupervised Image Classification and Segmentation`, >- `Learning Discrete Representations via Information Maximizing Self-Augmented Training`, >- [`Information based Deep Clustering: An experimental study`](https://github.com/jizongFox/DeepClusteringProject) + SemiSupervised classification for >- `Semi-Supervised Learning by Augmented Distribution Alignment`, >- `Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning`, >- `Temporal Ensembling for Semi-Supervised Learning`, >- `Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results` + SemiSupervised Segmentation for >- `Adversarial Learning for Semi-Supervised Semantic Segmentation`, >- `Semi-Supervised and Task-Driven Data Augmentation`, >- [`Deep Co-Training for Semi-Supervised Image Segmentation`](https://arxiv.org/abs/1903.11233) + Discretely-constrained CNN for >- [`Discretely-constrained deep network for weakly-supervised segmentation`](https://github.com/jizongFox/Discretly-constrained-CNN/), >- `Mutual information based segmentation on medical imaging` They are examples how to develop research framework with the assistance of our proposed `deep-clustering-toolbox`. ___ ### Playground Several papers have been implemented based on this framework. I store them in the `playground` folder. The papers include: >- [`Auto-Encoding Variational Bayes`](https://arxiv.org/abs/1312.6114) >- [`mixup: BEYOND EMPIRICAL RISK MINIMIZATION`](https://arxiv.org/pdf/1710.09412.pdf) >- [`MINE: Mutual Information Neural Estimation`](https://arxiv.org/abs/1801.04062) >- [`Averaging Weights Leads to Wider Optima and Better Generalization`](https://arxiv.org/pdf/1803.05407.pdf) >- [`THERE ARE MANY CONSISTENT EXPLANATIONS OF UNLABELED DATA: WHY YOU SHOULD AVERAGE`](https://arxiv.org/pdf/1806.05594.pdf) >- [`Prior-aware Neural Network for Partially-Supervised Multi-Organ Segmentation`](https://arxiv.org/abs/1904.06346) --- ### Installation ```bash git clone https://github.com/jizongFox/deep-clustering-toolbox.git cd deep-clustering-toolbox python setup install # for those who do not want to make changes immediately. # or python setup develop # for those who want to modify the code and make the impact immediate. ``` Or very simply ```bash pip install deepclustering ``` ### Citation If you feel useful for your project, please consider citing this work. ```latex @article{peng2019deep, title={Deep Co-Training for Semi-Supervised Image Segmentation}, author={Peng, Jizong and Estradab, Guillermo and Pedersoli, Marco and Desrosiers, Christian}, journal={arXiv preprint arXiv:1903.11233}, year={2019} } ```

نیازمندی

مقدار	نام
-	msgpack
-	numpy
-	torch
-	torchvision
-	Pillow
-	scikit-learn
-	behave
-	requests
-	scikit-image
-	pandas
-	easydict
-	matplotlib
==4.32.2	tqdm
==1.8.0	py
==0.3.1	pytest-remotedata
-	tensorboardX
-	tensorboard
-	opencv-python
-	medpy
-	pyyaml
-	termcolor
-	gpuqueue
-	gdown

نحوه نصب

نصب پکیج whl deepclustering-0.0.3:

pip install deepclustering-0.0.3.whl

نصب پکیج tar.gz deepclustering-0.0.3:

pip install deepclustering-0.0.3.tar.gz