Merge pull request #41 from Gregor-Mendel-Institute/1.2

Merge 1.2 > master

.github/workflows/docker_base.yml

@@ -0,0 +1,32 @@
+name: Docker Container (Base)
+
+on:
+  push:
+    paths:
+      - 'containers/base/Dockerfile'
+      - 'containers/base/environment.yml'
+
+jobs:
+  push_to_registry:
+    name: Push Docker image to GitHub Packages
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check out the repo
+        uses: actions/checkout@v2
+      - name: Push to Docker Hub
+        uses: docker/build-push-action@v1
+        with:
+          username: ${{ secrets.DOCKER_USER }}
+          password: ${{ secrets.DOCKER_PASSWORD }}
+          repository: beckerlab/aradeepopsis-base
+          path: containers/base
+          tag_with_ref: true
+      - name: Push to GitHub Packages
+        uses: docker/build-push-action@v1
+        with:
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+          registry: docker.pkg.github.com
+          repository: gregor-mendel-institute/aradeepopsis/aradeepopsis-base
+          path: containers/base
+          tag_with_ref: true

.github/workflows/docker_dpp.yml

@@ -0,0 +1,32 @@
+name: Docker Container (DPP)
+
+on:
+  push:
+    paths:
+      - 'containers/addons/dpp/Dockerfile'
+      - 'containers/addons/dpp/environment.yml'
+
+jobs:
+  push_to_registry:
+    name: Push Docker image to GitHub Packages
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check out the repo
+        uses: actions/checkout@v2
+      - name: Push to Docker Hub
+        uses: docker/build-push-action@v1
+        with:
+          username: ${{ secrets.DOCKER_USER }}
+          password: ${{ secrets.DOCKER_PASSWORD }}
+          repository: beckerlab/aradeepopsis-dpp
+          path: containers/addons/dpp
+          tag_with_ref: true
+      - name: Push to GitHub Packages
+        uses: docker/build-push-action@v1
+        with:
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+          registry: docker.pkg.github.com
+          repository: gregor-mendel-institute/aradeepopsis/aradeepopsis-dpp
+          path: containers/addons/dpp
+          tag_with_ref: true

.github/workflows/docker_shiny.yml

@@ -0,0 +1,32 @@
+name: Docker Container (Shiny)
+
+on:
+  push:
+    paths:
+      - 'containers/shiny/Dockerfile'
+      - 'containers/shiny/environment.yml'
+
+jobs:
+  push_to_registry:
+    name: Push Docker image to GitHub Packages
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check out the repo
+        uses: actions/checkout@v2
+      - name: Push to Docker Hub
+        uses: docker/build-push-action@v1
+        with:
+          username: ${{ secrets.DOCKER_USER }}
+          password: ${{ secrets.DOCKER_PASSWORD }}
+          repository: beckerlab/aradeepopsis-shiny
+          path: containers/shiny
+          tag_with_ref: true
+      - name: Push to GitHub Packages
+        uses: docker/build-push-action@v1
+        with:
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+          registry: docker.pkg.github.com
+          repository: gregor-mendel-institute/aradeepopsis/aradeepopsis-shiny
+          path: containers/shiny
+          tag_with_ref: true

.github/workflows/minimal_test.yml

@@ -9,7 +9,7 @@ on:
       - master
 
 jobs:
-  test:
+  CI:
     env:
       NXF_VER: ${{ matrix.nxf_ver }}
     runs-on: ubuntu-latest

CHANGELOG.md

@@ -1,5 +1,22 @@
 # Changelog
 
+## [v1.2](https://github.com/Gregor-Mendel-Institute/aradeepopsis/releases/tag/v1.2) - 2020-07-15
+
+* updated `shiny` dependency `1.4.0` > `1.5.0`
+* added a more informative log message if pipeline fails on systems with insufficient memory
+* added `--ignore_label` parameter to exclude a segmentation class for trait calculation.
+* added `--label_spec` parameter to allow for mapping of segmentation classes to pixel values of user-supplied segmentation masks. This is a requirement for the `--masks` parameter now.
+* updated base.config to avoid out-of-memory issues when running with `--multiscale`
+* added Dockerfile + Conda environment for DPP v2.1.0
+* factored out Shiny dependencies into separate container (should be easier to deploy as a hosted Shiny app now)
+* added `--model 'DPP'` and `--dpp_checkpoint` to allow for custom segmentation models, trained using the [Deep Plant Phenomics](https://github.com/p2irc/deepplantphenomics) framework
+* added `--masks` parameter to skip semantic segmentation and run trait extraction using user-supplied masks
+* fixed an issue where the pipeline would crash if the input image contains an alpha channel
+* updated configuration for CBE cluster
+* added log message to show current parameter settings when starting a pipeline run
+* updated `scikit-image` `0.16.2` > `0.17.2`
+* updated `imagemagick` dependency `7.0.9_27` > `7.0.10_23`
+
 ## [v1.1](https://github.com/Gregor-Mendel-Institute/aradeepopsis/releases/tag/v1.1) - 2020-05-13
 
 * disabled task error strategy for pipeline runs on local computers

README.md

@@ -1,7 +1,10 @@
 # ![araDeepopsis](assets/logo/logo.png)
 
+![Docker Container (Base)](https://github.com/Gregor-Mendel-Institute/aradeepopsis/workflows/Docker%20Container%20(Base)/badge.svg?branch=master)
+![Docker Container (Shiny)](https://github.com/Gregor-Mendel-Institute/aradeepopsis/workflows/Docker%20Container%20(Shiny)/badge.svg?branch=master)
+![Docker Docker (DPP)](https://github.com/Gregor-Mendel-Institute/aradeepopsis/workflows/Docker%20Container%20(DPP)/badge.svg?branch=master)
+
 ![](https://github.com/Gregor-Mendel-Institute/aradeepopsis/workflows/Integration%20test/badge.svg?branch=master)
-[![Docker](https://github.com/Gregor-Mendel-Institute/aradeepopsis/workflows/Docker%20build/badge.svg)](https://hub.docker.com/r/beckerlab/aradeepopsis/)
 [![Nextflow](https://img.shields.io/badge/nextflow-%E2%89%A520.01.0-important.svg)](https://www.nextflow.io/)
 [![conda](https://img.shields.io/badge/install%20with-conda-brightgreen.svg)](https://conda.io/)
 
@@ -40,8 +43,18 @@ Depending on the model of choice, the pipeline extracts relevant phenotypic info
 
 ![Traits](docs/img/traits.png)
 
+# Extensibility
+
+The pipeline has a modular character, also allowing the use of [custom models](docs/parameters.md#custom-models) obtained from the [Deep Plant Phenomics](https://github.com/p2irc/deepplantphenomics)<sup>[[7]](#ref7)</sup> framework for the semantic segmentation step.
+
+In addition, it is also possible to [feed](docs/parameters.md#--masks) the pipeline with segmentation masks obtained by other methods, while still making use the automated trait extraction and visualization capabilities of the pipeline.
+
 # Usage
 
+## Hardware requirements
+
+Running the pipeline with the provided models requires at least 6GB of memory for singlescale inference, and at least 12GB for [`--multiscale`](docs/parameters.md#--multiscale).
+
 ## Setting up the pipeline
 
 > Note: Windows users will have to set up the [WSL](https://docs.microsoft.com/en-us/windows/wsl/install-win10) first.
@@ -63,8 +76,7 @@ nextflow run Gregor-Mendel-Institute/aradeepopsis --images 'path/to/images/*{png
 ### Example to run on the CBE cluster using Singularity
 
 ```bash
-module load singularity/3.4.1
-module load nextflow/19.10.0
+module load nextflow/20.01.0
 
 nextflow run Gregor-Mendel-Institute/aradeepopsis --images 'path/to/images/*{png|jpg}' -profile cbe,singularity
 ```
@@ -75,6 +87,7 @@ nextflow run Gregor-Mendel-Institute/aradeepopsis --images 'path/to/images/*{png
 | ------------- | ------------- | ------------- |
 | [`--model`](docs/parameters.md#--model)  | `C` | `<Character>` |
 | [`--images`](docs/parameters.md#--images) | `None` | `<Path>` |
+| [`--masks`](docs/parameters.md#--masks) | `false` | `<Path>` |
 | [`--multiscale`](docs/parameters.md#--multiscale)| `false` | `<Boolean>` |
 | [`--chunksize`](docs/parameters.md#--chunksize) | `10` | `<Integer>` |
 | [`--ignore_senescence`](docs/parameters.md#--ignore_senescence) | `true` | `<Boolean>` |
@@ -102,4 +115,6 @@ A description of all traits is available [here](docs/output.md#Trait-table).
 
 > <a name="ref5">[5]</a> **shiny: Easy web applications in R**<br />Rstudio Inc. (2014)
 
-> <a name="ref6">[6]</a> **Digital photography provides a fast, reliable, and noninvasive method to estimate anthocyanin pigment concentration in reproductive and vegetative plant tissues**<br />Del Valle JC, Gallardo-López A, Buide ML, Whittall JB, Narbona E, 2018. Ecol Evol. 8(6):3064–76.
+> <a name="ref6">[6]</a> **Digital photography provides a fast, reliable, and noninvasive method to estimate anthocyanin pigment concentration in reproductive and vegetative plant tissues**<br />Del Valle JC, Gallardo-López A, Buide ML, Whittall JB, Narbona E, 2018. Ecol Evol. 8(6):3064–76.
+
+> <a name="ref7">[7]</a> **Deep Plant Phenomics: A Deep Learning Platform for Complex Plant Phenotyping Tasks**<br />Ubbens JR, Stavness I. Front Plant Sci. 2017 Jul 7;8:1190.

assets/shiny/app.R

@@ -28,13 +28,19 @@ options(shiny.maxRequestSize=20*1024^2)
 
 data <- read_csv("aradeepopsis_traits.csv")
 
+labels <- Sys.getenv(c("LABELS"),"class_background=0,class_norm=1,class_senesc=2,class_antho=3") %>% 
+  str_replace_all(.,"=[:digit:]+","") %>% 
+  str_split(.,",") %>% 
+  unlist() %>% 
+  tail(-1)
+
 imagenames <- data %>% select(file)
 invalid <- ifelse(file.exists('invalid_images.txt'),length(read_lines('invalid_images.txt')),0)
 traitcount <- ncol(data) - 2 # exclude filename and suffix
 imagecount <- nrow(data)
 
 # Define UI
-ui <- navbarPage(title="araDeepopsis", id="nav", theme = shinytheme("flatly"),
+ui <- navbarPage(title="aradeepopsis", id="nav", theme = shinytheme("flatly"),
 		tabPanel("Rosette Carousel",
 			sliderInput("chunk", label = "Select chunk:", min = 1, max = ceiling(imagecount/60), value = 1, width = '100%', step = 1),
 			slickROutput("slickr",width='100%',height='400px') %>% withSpinner()
@@ -89,7 +95,7 @@ ui <- navbarPage(title="araDeepopsis", id="nav", theme = shinytheme("flatly"),
 				actionButton("merge_data", "Analyze!"),
 				conditionalPanel(
 				  condition="input.tabset3 > 0",
-				  selectizeInput("exp_traits","Select Trait:", choices = colnames(data %>% select(-file,-format)), selected = "class_norm_area")
+				  selectizeInput("exp_traits","Select Trait:", choices = colnames(data %>% select(-file,-format)), selected = glue::glue("{labels[1]}_area"))
 				)
 			),
 			mainPanel(
@@ -98,7 +104,8 @@ ui <- navbarPage(title="araDeepopsis", id="nav", theme = shinytheme("flatly"),
 							tabPanel("Traits over time",value=1,plotOutput("timeline") %>% withSpinner())
 				)
 			)
-		)
+		),
+	tags$style(type = 'text/css', '.navbar .navbar-brand {font-variant: small-caps;}')
 )
 
 server <- function(input, output, session) {
@@ -149,7 +156,7 @@ server <- function(input, output, session) {
 		output$radar = renderChartJSRadar({
 			data %>%
 				filter(file == input$explorer_files) %>%
-				select(one_of(c("class_norm_area","class_antho_area","class_senesc_area"))) %>%
+				select(any_of(glue::glue("{labels}_area"))) %>%
 				pivot_longer(everything(),names_to = "Label") %>% 
 				mutate(value=value/sum(value)*100) %>% 
 				chartJSRadar(.,maxScale = 100,scaleStartValue = 0,scaleStepWidth = 25,showLegend = F)