Admin/logo (#301)

* fix test name

* add logos

---------

Co-authored-by: Benjamin Morris <[email protected]>
Co-authored-by: Benjamin Morris <[email protected]>

README.md

@@ -1,30 +1,41 @@
 <div align="center">
 
-# cyto-dl
+<picture>
+  <source media="(prefers-color-scheme: dark)" srcset="https://github.com/AllenCellModeling/cyto-dl/blob/b73e6f357727e3b42adea8540c86f2475ea60379/docs/CytoDL-logo-1C-onDark.png">
+  <source media="(prefers-color-scheme: light)" srcset="https://github.com/AllenCellModeling/cyto-dl/blob/b73e6f357727e3b42adea8540c86f2475ea60379/docs/CytoDL-logo-1C-onLight.png">
+  <img src="https://github.com/AllenCellModeling/cyto-dl/blob/b73e6f357727e3b42adea8540c86f2475ea60379/docs/CytoDL-logo-1C-onLight.png">
+</picture>
 
 <a href="https://pytorch.org/get-started/locally/"><img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-ee4c2c?logo=pytorch&logoColor=white"></a>
 <a href="https://pytorchlightning.ai/"><img alt="Lightning" src="https://img.shields.io/badge/-Lightning-792ee5?logo=pytorchlightning&logoColor=white"></a>
 <a href="https://hydra.cc/"><img alt="Config: Hydra" src="https://img.shields.io/badge/Config-Hydra-89b8cd"></a>
 <a href="https://github.com/ashleve/lightning-hydra-template"><img alt="Template" src="https://img.shields.io/badge/-Lightning--Hydra--Template-017F2F?style=flat&logo=github&labelColor=gray"></a><br>
 
-<!--[![Paper](http://img.shields.io/badge/paper-arxiv.1001.2234-B31B1B.svg)](https://www.nature.com/articles/nature14539)
-[![Conference](http://img.shields.io/badge/AnyConference-year-4b44ce.svg)](https://papers.nips.cc/paper/2020) -->
-
 </div>
 
 <p align="center">
-  <img src="docs/overview.png" width="100%" title="project overview">
+  <picture>
+    <source media="(prefers-color-scheme: dark)" srcset="https://github.com/AllenCellModeling/cyto-dl/blob/acf7dad69f492c417b0e486f8f08c19f25575927/docs/CytoDL-overview_dark_1.png">
+    <source media="(prefers-color-scheme: light)" srcset="https://github.com/AllenCellModeling/cyto-dl/blob/acf7dad69f492c417b0e486f8f08c19f25575927/docs/CytoDL-overview_light_1.png">
+    <img src="https://github.com/AllenCellModeling/cyto-dl/blob/acf7dad69f492c417b0e486f8f08c19f25575927/docs/CytoDL-overview_light_1.png">
+  </picture>
 </p>
 
 ## Description
 
-In an effort to spend more work on methods development, simplify maintenance,
-and create a unified framework for all of AICS's deep learning tools, we have
-created `cyto-ml`. As the underlying framework is based on [lightning-hydra-template](https://github.com/ashleve/lightning-hydra-template), we recommend that you familiarize yourself with their (short) docs for detailed instructions on running training, overrides, etc.
+As part of the [Allen Institute for Cell Science's](allencell.org) mission to understand the principles by which human induced pluripotent stem cells establish and maintain robust dynamic localization of cellular structure, `CytoDL` aims to unify deep learning approaches for understanding 2D and 3D biological data as images, point clouds, and tabular data.
+
+The bulk of `CytoDL`'s underlying structure bases the [lightning-hydra-template](https://github.com/ashleve/lightning-hydra-template) organization - we highly recommend that you familiarize yourself with their (short) docs for detailed instructions on running training, overrides, etc.
+
+Our currently available code is roughly split into two domains: image-to-image transformations and representation learning. The image-to-image code (denoted im2im) contains configuration files detailing how to train and predict using models for resolution enhancement (e.g. predicting 100x images from 20x images), semantic and instance segmentation, and label-free prediction. Representation learning code includes a wide variety of Variational Auto Encoder (VAE) architectures.
+
+As we rely on recent versions of pytorch, users wishing to train and run models on GPU hardware will need up-to-date NVIDIA drivers. Users with older GPUs should not expect code to work out of the box. Similarly, we do not currently support training/predicting on Mac GPUs. In most cases, cpu-based training should work when GPU training fails.
+
+For Im2Im models, we provide a handful of example 3D images for training the basic image-to-image tranformation-type models and default model configuration files for users to become comfortable with the framework and prepare them for training and applying these models on their own data.
 
 ## How to run
 
-Install dependencies
+Install dependencies. Dependencies are platform specific, please replace `PLATFORM` with your platform - either `linux`, `windows`, or `mac`
 
 ```bash
 # clone project
@@ -35,16 +46,16 @@ cd cyto-dl
 conda create -n myenv python=3.9
 conda activate myenv
 
-pip install -r requirements/linux/requirements.txt
+pip install -r requirements/PLATFORM/requirements.txt
 
 # [OPTIONAL] install extra dependencies - equivariance related
-pip install -r requirements/linux/equiv-requirements.txt
+pip install -r requirements/PLATFORM/equiv-requirements.txt
 
 pip install -e .
 
 
 #[OPTIONAL] if you want to use default experiments on example data
-python scripts/download_test_data.py
+python scripts download_test_data.py
 ```
 
 Train model with chosen experiment configuration from [configs/experiment/](configs/experiment/)

tests/conftest.py

@@ -13,7 +13,7 @@
 OmegaConf.register_new_resolver("eval", eval)
 
 # Experiment configs to test
-experiment_types = ["instance_segmentation", "gan", "segmentation", "labelfree"]
+experiment_types = ["instance_seg", "gan", "segmentation", "labelfree"]
 
 
 @pytest.fixture(scope="package", params=experiment_types)