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cellshape-cloud

https://github.com/sentinal4d/cellshape-cloud

Science Score: 44.0%

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    Scientific vocabulary similarity
    Low similarity (14.0%) to scientific vocabulary
Last synced: 7 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: Sentinal4D
  • License: bsd-3-clause
  • Language: Python
  • Default Branch: main
  • Size: 99.4 MB
Statistics
  • Stars: 6
  • Watchers: 1
  • Forks: 3
  • Open Issues: 4
  • Releases: 0
Created about 4 years ago · Last pushed 8 months ago
Metadata Files
Readme Contributing License Code of conduct Citation

README.md

Python Version PyPI Downloads Wheel Development Status Tests Coverage Status Code style: black

Cellshape logo by Matt De Vries

Cellshape-cloud is an easy-to-use tool to analyse the shapes of cells using deep learning and, in particular, graph-neural networks. The tool provides the ability to train popular graph-based autoencoders on point cloud data of 2D and 3D single cell masks as well as providing pre-trained networks for inference.

To install

bash pip install cellshape-cloud

Usage

Basic Usage

```python import torch from cellshape_cloud import CloudAutoEncoder

model = CloudAutoEncoder(numfeatures=128, k=20, encodertype="dgcnn", decoder_type="foldingnet")

points = torch.randn(1, 2048, 3)

recon, features = model(points) ```

To train an autoencoder on a set of point clouds created using cellshape-helper:

```python import torch from torch.utils.data import DataLoader

import cellshapecloud as cloud from cellshapecloud.vendor.chamfer_distance import ChamferLoss

inputdir = "path/to/pointcloud/files/" batchsize = 16 learningrate = 0.0001 numepochs = 1 output_dir = "path/to/save/output/"

model = cloud.CloudAutoEncoder(numfeatures=128, k=20, encodertype="dgcnn", decoder_type="foldingnet")

dataset = cloud.PointCloudDataset(input_dir)

dataloader = DataLoader(dataset, batchsize=batchsize, shuffle=True)

criterion = ChamferLoss()

optimizer = torch.optim.Adam( model.parameters(), lr=learningrate * 16 / batchsize, betas=(0.9, 0.999), weight_decay=1e-6, )

cloud.train(model, dataloader, numepochs, criterion, optimizer, outputdir) ```

Parameters

  • num_features: int.
    The size of the latent space of the autoencoder.
  • k: int.
    The number of neightbours to use in the k-nearest-neighbours graph construction.
  • encoder_type: str.
    The type of encoder: 'foldingnet' or 'dgcnn'
  • decoder_type: str.
    The type of decoder: 'foldingnet' or 'dgcnn'

References

[1] An Tao, 'Unsupervised Point Cloud Reconstruction for Classific Feature Learning', GitHub Repo, 2020

Owner

  • Name: Sentinal4D
  • Login: Sentinal4D
  • Kind: organization
  • Email: mattdevries.ai@gmail.com
  • Location: United Kingdom

Citation (CITATION.cff) 

cff-version: 0.1.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "De Vries"
  given-names: "Matt"
  orcid: "https://orcid.org/0000-0002-4098-1611"
title: "cellshape-cloud"
version: 0.1.0
date-released: 2022-09-13
url: "https://github.com/Sentinal4D/cellshape-cloud"

GitHub Events

Total
  • Push event: 2
Last Year
  • Push event: 2

Committers

Last synced: about 3 years ago

All Time
  • Total Commits: 235
  • Total Committers: 5
  • Avg Commits per committer: 47.0
  • Development Distribution Score (DDS): 0.132
Top Committers
Name Email Commits
DeVriesMatt m****3@g****m 204
Adam Tyson c****e@a****m 19
Matt De Vries 4****t@u****m 9
kapoorlab r****r@g****m 2
Matt De Vries m****i@g****m 1
Committer Domains (Top 20 + Academic)
adamltyson.com: 1

Issues and Pull Requests

Last synced: 8 months ago

All Time
  • Total issues: 6
  • Total pull requests: 8
  • Average time to close issues: 3 months
  • Average time to close pull requests: about 16 hours
  • Total issue authors: 4
  • Total pull request authors: 3
  • Average comments per issue: 1.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 8
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • kapoorlab (2)
  • adamltyson (2)
  • DeVriesMatt (1)
  • ScarWar (1)
Pull Request Authors
  • DeVriesMatt (4)
  • adamltyson (3)
  • kapoorlab (1)
Top Labels
Issue Labels
enhancement (1) help wanted (1) good first issue (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 409 last-month
  • Total dependent packages: 4
  • Total dependent repositories: 1
  • Total versions: 48
  • Total maintainers: 3
pypi.org: cellshape-cloud

3D cell shape analysis using geometric deep learning on point clouds

  • Versions: 48
  • Dependent Packages: 4
  • Dependent Repositories: 1
  • Downloads: 409 Last month
Rankings
Dependent packages count: 3.3%
Downloads: 12.2%
Average: 15.1%
Forks count: 15.5%
Stargazers count: 21.8%
Dependent repos count: 22.6%
Maintainers (3)
adamltyson DeVriesMatt somaSystems
Last synced: 8 months ago

Dependencies

.github/workflows/test_and_deploy.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
  • actions/setup-python v1 composite
pyproject.toml pypi
setup.py pypi