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 license: mit
 ---
-<p align="center">
-<img src = "https://raw.githubusercontent.com/DevoLearn/devolearn/master/images/banner_1.jpg">
-</p>
-![Build Status](https://github.com/DevoLearn/devolearn/actions/workflows/main.yml/badge.svg)
-[![codecov](https://codecov.io/gh/DevoLearn/devolearn/branch/master/graph/badge.svg?token=F8AJZSGWXJ)](https://codecov.io/gh/DevoLearn/devolearn)
-[![](https://img.shields.io/github/issues/DevoLearn/devolearn)](https://github.com/DevoLearn/devolearn/issues)
-[![](https://img.shields.io/github/contributors/DevoLearn/devolearn)](https://github.com/DevoLearn/devolearn/graphs/contributors)
-[![](https://img.shields.io/github/last-commit/DevoLearn/devolearn)](https://github.com/DevoLearn/devolearn/commits/master)
-[![](https://img.shields.io/twitter/url?color=green&label=Slack&logo=slack&logoColor=blue&style=social&url=https%3A%2F%2Fopenworm.slack.com%2Farchives%2FCMVFU7Q4W)](https://openworm.slack.com/archives/CMVFU7Q4W)
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/DevoLearn/data-science-demos/blob/master/devolearn_docs/devolearn_quickstart.ipynb)
-## Contents
-* [Example notebooks](https://github.com/DevoLearn/devolearn#example-notebooks)
-* [Segmenting the C. elegans embryo](https://github.com/DevoLearn/devolearn#segmenting-the-c-elegans-embryo)
-* [Generating synthetic images of embryos with a GAN](https://github.com/DevoLearn/devolearn#generating-synthetic-images-of-embryos-with-a-pre-trained-gan)
-* [Predicting populations of cells within the C. elegans embryo](https://github.com/DevoLearn/devolearn#predicting-populations-of-cells-within-the-c-elegans-embryo)
-* [Contributing to DevoLearn](https://github.com/DevoLearn/devolearn/blob/master/.github/contributing.md#contributing-to-devolearn)
-* [Links to datasets](https://github.com/DevoLearn/devolearn#links-to-datasets)
-* [Contact us](https://github.com/DevoLearn/devolearn#authorsmaintainers)
-### Installation
-```python
-pip install devolearn
-```
-### Example notebooks
-<p align="center">
-<img src = "https://raw.githubusercontent.com/DevoLearn/data-science-demos/master/Networks/nodes_matrix_long_smooth.gif" width = "40%">
-<img src = "https://raw.githubusercontent.com/DevoLearn/data-science-demos/master/Networks/3d_node_map.gif" width = "40%">
-</p>
-* [Extracting centroid maps and making 3d centroid models](https://nbviewer.jupyter.org/github/DevoLearn/data-science-demos/blob/master/Networks/experiments_with_devolearn_node_maps.ipynb)
-### Segmenting the Cell Membrane in C. elegans embryo
-<p align="center">
-<img src = "https://raw.githubusercontent.com/DevoLearn/devolearn/master/images/pred_centroids.gif" width = "80%">
-</p>
-* Importing the model
-```python
-from devolearn import cell_membrane_segmentor
-segmentor = cell_membrane_segmentor()
-```
-* Running the model on an image and viewing the prediction
-```python
-seg_pred = segmentor.predict(image_path = "sample_data/images/seg_sample.jpg")
-plt.imshow(seg_pred)
-plt.show()
-```
-* Running the model on a video and saving the predictions into a folder
-```python
-filenames = segmentor.predict_from_video(video_path = "sample_data/videos/seg_sample.mov", centroid_mode = False, save_folder = "preds")
-```
-* Finding the centroids of the segmented features
-```python
-seg_pred, centroids = segmentor.predict(image_path = "sample_data/images/seg_sample.jpg", centroid_mode = True)
-plt.imshow(seg_pred)
-plt.show()
-```
-* Saving the centroids from each frame into a CSV
-```python
-df = segmentor.predict_from_video(video_path = "sample_data/videos/seg_sample.mov", centroid_mode = True, save_folder = "preds")
-df.to_csv("centroids.csv")
-```
-### Segmenting the Cell Nucleus in C. elegans embryo
-<p align="center">
-<img src = "https://huggingface.co/spaces/devoworm-group/README/blob/main/images/nucleus_segmentation.gif" width = "50%">
-</p>
-* Importing the model
-```python
-from devolearn import cell_nucleus_segmentor
-segmentor = cell_nucleus_segmentor()
-```
-* Running the model on an image and viewing the prediction
-```python
-seg_pred = segmentor.predict(image_path = "sample_data/images/nucleus_seg_sample.jpg")
-plt.imshow(seg_pred)
-plt.show()
-```
-### Generating synthetic images of embryos with a Pre-trained GAN
-<p align="center">
-<img src = "https://raw.githubusercontent.com/devoworm/GSoC-2020/master/Pre-trained%20Models%20(DevLearning)/images/generated_embryos_3.gif" width = "30%">
-</p>
-* Importing the model
-```python
-from devolearn import Generator, embryo_generator_model
-generator = embryo_generator_model()
-```
-* Generating a picture and viewing it with [matplotlib](https://matplotlib.org/)
-```python
-gen_image = generator.generate()
-plt.imshow(gen_image)
-plt.show()
-```
-* Generating n images and saving them into `foldername` with a custom size
-```python
-generator.generate_n_images(n = 5, foldername= "generated_images", image_size= (700,500))
-```
----
-### Predicting populations of cells within the C. elegans embryo
-<p align="center">
-<img src = "https://raw.githubusercontent.com/devoworm/GSoC-2020/master/Pre-trained%20Models%20(DevLearning)/images/resnet_preds_with_input.gif" width = "60%">
-</p>
-* Importing the population model for inferences
-```python
-from devolearn import lineage_population_model
-```
-* Loading a model instance to be used to estimate lineage populations of embryos from videos/photos.
-```python
-model = lineage_population_model(device = "cpu")
-```
-* Making a prediction from an image
-```python
-print(model.predict(image_path = "sample_data/images/embryo_sample.png"))
-```
-* Making predictions from a video and saving the predictions into a CSV file
-```python
-results = model.predict_from_video(video_path = "sample_data/videos/embryo_timelapse.mov", save_csv = True, csv_name = "video_preds.csv", ignore_first_n_frames= 10, ignore_last_n_frames= 10, postprocess = False)
-```
-* Plotting the model's predictions from a video
-```python
-plot = model.create_population_plot_from_video(video_path = "sample_data/videos/embryo_timelapse.mov", save_plot= True, plot_name= "plot.png", ignore_last_n_frames= 0, postprocess = False)
-plot.show()
-```
-## Links to Datasets
-| **Model**                                       | **Data source**                                                                                                                                                   |
-|-------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| Segmenting the cell membrane in C. elegans embryo                | [3DMMS: robust 3D Membrane Morphological Segmentation of C. elegans embryo](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2720-x#Abs1/) |
-| Segmenting the nucleus in C. elegans embryo    | [C. elegans Cell-Tracking-Challenge dataset](http://celltrackingchallenge.net/3d-datasets/)
-| Cell lineage population prediction + embryo GAN | [EPIC dataset](https://epic.gs.washington.edu/)
-## Authors/maintainers:
-* [Mayukh Deb](https://twitter.com/mayukh091)
-* [Ujjwal Singh](https://twitter.com/ujjjwalll)
-* [Dr. Bradly Alicea](https://twitter.com/balicea1)
-Feel free to join our [Slack workspace](https://openworm.slack.com/archives/CMVFU7Q4W)!

 license: mit
 ---
+# DevoWorm
+The DevoWorm group website is located at [devoworm.weebly.com](http://devoworm.weebly.com/). The website features links to
+educational, academic, media-related and collaborative opportunities associated with the project. The DevoZoo is located at [devoworm.github.io](http://devoworm.github.io), and features content relevant to community education and engagement. DevoWorm is affiliated with the [OpenWorm Foundation](http://www.openworm.org/) and the [Orthogonal Research Laboratory](http://orthogonal-research.weebly.com/). We engage in Open Science, an encourage the use of Jupyter Notebooks, short video descriptions of research, and demos.
+## Roadmap
+DevoWorm is currently divided into three loosely-knit interest areas: developmental dynamics, cybernetics and digital morphogenesis, and reproduction and developmental plasticity. While our main interest is in the nematode *Caenorhabditis elegans*, we are also interested in cross-species comparative work. We also have three additional types of initiative which cross-cut the interest areas: theory-building, education, and open science. These initiatives are infused into our interest areas.
+**Developmental Dynamics** currently involves using secondary data collected from embryos along with bioinformatic and data science techniques to answer questions regarding the process of early embryogenesis and the timing of later morphogenesis. To address these problems, we have used number of innovative approaches.
+**Cybernetics and Digital Morphogenesis** has involved using platforms such as Morphozoic and theoretical approaches such as Multicell Systems and Braitenberg Vehicles to better understand physical interactions during embryogenesis and morphogenesis. We have also explored the use of cybernetic models and concepts to better understand the general process of embryogenesis.
+**Reproduction and Developmental Plasticity** involves utilizing an evo-devo approach to understand *Caenorhabditis elegans* more generally. Our existing datasets and papers include a focus on larval development and life-history processes. This area of the project also features primary empirical data, based on formal experimental design.
+Objective                                        | Examples
+---                                              | ---
+Developmental Dynamics (DD)                      |
+DD                                               | [Comparative Quantitative Embryogenesis](http://www.mdpi.com/2079-7737/5/3/33)
+DD                                               | [Differentiation Trees and Maps](http://www.biorxiv.org/content/early/2016/07/07/062539)
+DD                                               | [Embryo Networks and Developmental Connectomes](https://doi.org/10.1101/146035)
+DD                                               | [Time-series of Terminal Differentiation](https://www.biorxiv.org/content/early/2018/03/14/282004)
+Cybernetics and Digital Morphogenesis (C-DM)     |
+C-DM                                             | [Morphozoic (Cellular Automata)](https://www.researchgate.net/publication/311738597_Morphozoic_Cellular_Automata_with_Nested_Neighborhoods_as_a_Metamorphic_Representation_of_Morphogenesis)
+C-DM                                             | [Multicell Systems](https://github.com/Orthogonal-Research-Lab/origins-embryo/tree/master/Multicell%20Systems)
+C-DM                                             | [Braitenberg's Vehicles and Games](https://www.sciencedirect.com/science/article/pii/S0303264718302065?via%3Dihub)
+Reproduction and Developmental Plasticity (R-DP) |
+R-DP                                             | [Experimental Evolution](http://rsos.royalsocietypublishing.org/content/3/11/160496)
+R-DP                                             | [Life-history Plasticity](http://www.biorxiv.org/content/early/2016/03/24/045609)
+R-DP                                             | [Dynamical Heterochrony](https://github.com/Orthogonal-Research-Lab/Developmental-Incongruities-and-Heterochrony/blob/master/Developmental-Incongruity-Heterochrony.md)
+## Repos in DevoWorm Github
+Repo Name                                                                       | Description
+---                                                                             | ---
+[DevoWorm](https://github.com/devoworm/DevoWorm)                                | Basic Secondary _C. elegans_ Embryogenetic Data
+[Embryo Segmentation](https://github.com/devoworm/EmbryoSegmentation)           | Embryo Segmentation Software (GSoC 2017)
+[Devlopmental XML and Networks](https://github.com/devoworm/GSoC-2018)          | Developmental XML and Networks (GSoC 2018)
+[Semantic Phenotypes](https://github.com/devoworm/GSOC-2019)                    | Semantic Phenotypes (GSoC 2019)
+[CC3D](https://github.com/devoworm/CC3D-local)                                  | CompuCell 3D Models
+[Embryogenetic Connectome](https://github.com/devoworm/embryogenetic-connectome)| Embryogenetic Connectome Analysis
+[Assorted Notebooks](https://github.com/devoworm/devoworm.github.io)            | Project-related Jupyter Notebooks
+[Graphical Visualization](https://github.com/devoworm/Graph-Code)               | Code for Graph Creation
+[Datasets and Analysis](https://github.com/devoworm/DevoWorm)                   | Tools for Developmental Data Science
+[Morphozoic](https://github.com/devoworm/Morphozoic)                            | Morphozoic Models
+[Analysis of Developmental Trees (AoDT)](https://github.com/devoworm/AoDT)      | Analysis of Developmental Trees (AoDT)
+[OW-DW Education](https://github.com/devoworm/OW-DW-Education)                  | OpenWorm-DevoWorm Education (Curriculum-building)
+[TSMs](https://github.com/devoworm/Triangular-State-Machines-TSM)               | Triangular State Machine (TSMs)
+[Zebrafish Embryo](https://github.com/devoworm/zebrafish-embryo)                | Zebrafish Embryo
+[_n_-D Visualization](https://github.com/devoworm/nD-visualization)             | n-D Visualization
+[Drosophila Imaginal Disc Segmentation](https://github.com/devoworm/Drosophila-imaginal-disc-segmentation)|Drosophila Imaginal Disc Segmentation
+[Drosophila Embryo (fused cell centroids)](https://github.com/devoworm/Drosophila-embryo-fused-cell-centroids)|Drosophila Embryo (fused cell centroids)
+[Digital _Bacillaria_](https://github.com/devoworm/Digital-Bacillaria)            | Quantifying _Bacillaria_ (Diatom) Phenotypes
+[Mouse Embryo (Zygote to Blastocyst)](https://github.com/devoworm/Mouse-Embryo-Zygote-to-Blastocyst) | Data from Early Mouse Embryo
+[DW-ML](https://github.com/devoworm/DW-ML) | DevoWormML (interest area for applied Machine Learning)
+[AoDT](https://github.com/devoworm/AoDT) | Analysis of Developmental Trees
+[Compositionality](https://github.com/devoworm/Compositionality) | Compositionality and Category Theory as Applied to Development
+[Macro-Mechanisms for Embryogenesis](https://github.com/devoworm/Macro-mechanisms-for-Embryogenesis) | Collective Mechanisms of Morphogenesis in Embryos
+[Experimental Evolution](https://github.com/devoworm/Experimental-Evolution) | Experimental Evolution in _C. elegans_
+[Triangular State Machines - TSM](https://github.com/devoworm/Triangular-State-Machines-TSM) | Theoretical Gene Expression Network Motifs
+[Theoretical-Types-of-Embryo-Developmental-Networks](https://github.com/devoworm/Theoretical-Types-of-Embryo-Developmental-Networks) | Graph Theory as Applied to Development
+[Raising the Worm Brain](https://github.com/devoworm/Raising-the-Worm-Brain) | Functional Developmental Connectomes
+[Emergent Behavior](https://github.com/devoworm/Emergent-Behavior) | Behavioral Emergence in Development