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app.R
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# create dir
dir.name <- 'www'
if (!dir.exists(dir.name)){
dir.create(dir.name, recursive = TRUE, showWarnings = FALSE)
}
shiny::addResourcePath(prefix = "www", directoryPath = "www")
# copy favicon folder to the www dir
R.utils::copyDirectory(from = "favicon_io", to = file.path(dir.name, "favicon_io"))
# if (!require("BiocManager", quietly = TRUE))
# install.packages("BiocManager")
# BiocManager::install("EBImage")
# remotes::install_github("r-spatial/sf")
# load libraries
library(dplyr)
library(htmltools)
library(BiocManager)
library(EBImage)
# source all scripts
source("f_border.R", local = TRUE)
source("f_meas.R", local = TRUE)
source("f_process_color.R", local = TRUE)
source("f_process_detrend.R", local = TRUE)
source("f_process_equalization.R", local = TRUE)
source("f_process_filter.R", local = TRUE)
source("f_process_morphological.R", local = TRUE)
source("f_process_threshold.R", local = TRUE)
source("f_process_track.R", local = TRUE)
source("f_track_all.R", local = TRUE)
source("f_track_first.R", local = TRUE)
source("us_track.R", local = TRUE)
# use this code to debug
# rsconnect::showLogs()
ui <- shiny::fluidPage(
# add favicon
shiny::tags$head(
shiny::tags$link(rel = "shortcut icon", href = "www/favicon_io/favicon.ico"),
shiny::tags$link(rel = "shortcut icon", href = "www/favicon_io/android-chrome-192x192.png"),
shiny::tags$link(rel = "shortcut icon", href = "www/favicon_io/android-chrome-512x512.png"),
shiny::tags$link(rel = "apple-touch-icon", href = "www/favicon_io/apple-touch-icon.png"),
shiny::tags$link(rel = "icon", href = "www/favicon_io/favicon-16x16.png"),
shiny::tags$link(rel = "icon", href = "www/favicon_io/favicon-32x32.png"),
shiny::tags$link(rel = "shortcut icon", href = "www/favicon_io/favicon.ico"),
),
# add font awesome
tags$head(
tags$link(rel = "stylesheet", href = "https://maxcdn.bootstrapcdn.com/font-awesome/4.7.0/css/font-awesome.min.css")
),
# use shinythemes
theme = shinythemes::shinytheme("flatly"),
# use shinyjs
shinyjs::useShinyjs(),
# status bar
shinybusy::add_busy_bar(color = "#FF0000"),
# Application title
shiny::titlePanel(
shiny::fluidRow(
shiny::column(
8,
list(
fontawesome::fa("wifi"),
shiny::HTML("<strong>UsIA</strong>"),
shiny::br(),
"Ultrasound Image Analysis"
),
style = "text-align:left;"
),
shiny::column(
4,
tags$a(
id = "restart",
class = "btn btn-primary",
href = "javascript:history.go(0)",
shiny::HTML('<i class="fa fa-refresh fa-1x"></i>'),
title = "restart",
style = "color:white; border-color:white; border-radius:100%"
),
style = "text-align:right;"
)
),
windowTitle = "UsIA | Ultrasound Image Analysis"
),
shiny::HTML(
"<a href=\"https://doi.org/10.5281/zenodo.10439718\" style=\"vertical-align:middle;\"><img src=\"https://zenodo.org/badge/DOI/10.5281/zenodo.10439718.svg\" alt=\"DOI\" style=\"vertical-align:top;\"></a>"
),
shiny::br(),
shiny::br(),
# change color of fileInput button
tags$head(tags$style(
shiny::HTML(".btn-file {background-color: #2C3E50;}")
)),
# Main panel for displaying outputs ----
shiny::tabsetPanel(
id = "tabs",
type = "tabs",
shiny::tabPanel(
title = list(fontawesome::fa("right-to-bracket"), "Input"),
shiny::br(),
shiny::fileInput(
inputId = "InputFile",
label = NULL,
multiple = FALSE,
buttonLabel = list(fontawesome::fa("file-video"), "Upload"),
accept = c(".mp4"),
width = "100%",
),
shiny::tabsetPanel(
id = "tabInput",
type = "tabs",
shiny::tabPanel(
title = list(fontawesome::fa("video"), "Video"),
shiny::br(),
shiny::uiOutput(outputId = "videoraw"),
align = "center"
),
shiny::tabPanel(
title = list(fontawesome::fa("edit"), "Edit"),
shiny::br(),
shiny::sliderInput(
inputId = "framesEdit",
label = NULL,
min = 1,
max = 100,
value = c(1, 100),
step = 1,
ticks = FALSE,
animate = TRUE,
width = "100%"
),
shiny::uiOutput(outputId = "videoedit"),
align = "center"
),
),
),
shiny::tabPanel(
title = list(fontawesome::fa("ruler"), "Measure"),
shiny::br(),
shiny::tabsetPanel(
id = "tabMeasure",
type = "tabs",
shiny::tabPanel(
title = list(fontawesome::fa("image"), "Frame"),
shiny::br(),
# split two columns
shiny::fluidRow(
shiny::column(
4,
shiny::sliderInput(
inputId = "imgEdit",
label = "Frame",
min = 1,
max = 100,
value = 1,
step = 1,
ticks = FALSE,
animate = TRUE,
width = "100%"
),
shiny::numericInput(
inputId = "imgScale",
label = "Scale (mm)",
value = 1,
min = 0.1,
max = 10,
step = 0.1,
width = "100%"
),
shiny::br(),
shiny::actionButton(
inputId = "reset",
label = "Reset ROI",
width = "100%"),
shiny::br(),
htmltools::h5(htmltools::strong("Click"), " on plot to start. ", htmltools::strong("Move"), " the cursor to draw the ROI. ", htmltools::strong("Click"), " again to stop."),
shiny::br(),
align = "center"
),
shiny::column(
8,
shiny::plotOutput(
outputId = "plotMeasure",
width = "auto",
click = "img_click",
hover = shiny::hoverOpts(
id = "hover",
delay = 100,
delayType = "throttle",
clip = TRUE,
nullOutside = TRUE
)
),
),
),
align = "center"
),
shiny::tabPanel(
title = list(fontawesome::fa("table"), "Tables"),
shiny::br(),
DT::dataTableOutput("tableMeasure", width = "100%"),
align = "center"
),
),
),
shiny::tabPanel(
title = list(fontawesome::fa("arrow-trend-up"), "Track"),
shiny::br(),
shiny::tabsetPanel(
id = "tabTrack",
type = "tabs",
shiny::tabPanel(
title = list(fontawesome::fa("sliders"), "Setup"),
shiny::br(),
# split two columns
shiny::fluidRow(
shiny::column(
4,
shiny::sliderInput(
inputId = "KernelSizeTrack",
label = "Object (px)",
min = 1,
max = 201,
value = 50,
step = 2,
ticks = FALSE,
width = "100%",
),
shiny::sliderInput(
inputId = "Overlap",
label = "ROI (%)",
min = 0,
max = 100,
value = 50,
step = 5,
ticks = FALSE,
width = "100%",
),
shiny::radioButtons(
inputId = "FilterType",
label = "Filter",
choices = c("none", "mean", "median"),
selected = "none",
inline = TRUE,
width = "100%"
),
shiny::sliderInput(
inputId = "FilterSize",
label = "Size (px)",
min = 1,
max = 11,
value = 1,
step = 2,
ticks = FALSE,
width = "100%",
),
shiny::sliderInput(
inputId = "Jump",
label = "Jump (frames)",
min = 0,
max = 5,
value = 0,
ticks = FALSE,
width = "100%",
),
shiny::br(),
shiny::actionButton(
inputId = "buttAnalyze",
label = "Analyze",
class = "btn-primary",
style = "width:100%; border-color:white; border-radius: 10px",
icon("play")
),
shiny::br(),
align = "center"
),
shiny::column(
8,
shiny::tabPanel(
title = list(fontawesome::fa("crop"), "ROI"),
shiny::br(),
shiny::plotOutput(
outputId = "plotROI",
width = "auto",
click = "roi_click"
),
align = "center"
),
),
),
),
shiny::tabPanel(
value = "track",
title = list(fontawesome::fa("right-from-bracket"), "Output"),
shiny::br(),
shiny::downloadButton(
outputId = "downloadMP4",
label = "Video",
class = "btn-primary",
style = "width:100%; border-color:white; border-radius: 10px;",
),
shiny::br(),
shiny::br(),
shiny::uiOutput(outputId = "videooutput"),
align = "center"
),
shiny::tabPanel(
title = list(fontawesome::fa("chart-line"), "Plots"),
shiny::br(),
shiny::fluidPage(
shiny::fluidRow(
shiny::column(
4,
shiny::downloadButton(
outputId = "downloadPATH",
label = "Trajectory data",
class = "btn-primary",
style = "width:100%; border-color:white; border-radius: 10px;",
),
),
shiny::column(
4,
shiny::downloadButton(
outputId = "downloadDISPL",
label = "Displacement data",
class = "btn-primary",
style = "width:100%; border-color:white; border-radius: 10px;",
),
),
shiny::column(
4,
shiny::downloadButton(
outputId = "downloadCC",
label = "Cross-correlation data",
class = "btn-primary",
style = "width:100%; border-color:white; border-radius: 10px;",
),
align = "center"
),
),
),
shiny::br(),
shiny::br(),
shiny::plotOutput("plotTrack", width = "100%"),
align = "center"
),
shiny::tabPanel(
title = list(fontawesome::fa("table"), "Tables"),
shiny::br(),
DT::dataTableOutput("tableTrack", width = "100%"),
align = "center"
),
),
),
shiny::tabPanel(
title = list(fontawesome::fa("circle-info")),
shiny::br(),
shiny::HTML(
"<p>1. Upload a video file (.mp4) with the <b>Upload video</b>.</p>
<p>2. If necessary, edit the video by subsetting the uploaded video using <b>Edit</b>.</p>
<p>3. Click <b>Track</b> to configure the analysis.</p>
<p>4. Set up the parameters for analysis:</p>
<p> - <i>Object size</i>: '1' to '201' (odd numbers only).</p>
<p> - <i>Overlap</i>: '0' to '100%'.</p>
<p> - <i>Filter type</i>: 'none', 'gaussian', 'median'.</p>
<p> - <i>Filter size</i>: '1' to '11' (odd numbers only).</p>
<p> - <i>Jump</i>: '1' to '5' frames.</p>
<p>5. Set the region of interest (<b>ROI</b>) for analysis. Click on the screen to mark the center of the ROI.</p>
<p>6. Click <b>Analyze</b>. Wait until the red progress bar on the top stops blinking.</p>
<p>7. Check <b>Output</b> tab to visualize the processed video.</p>
<p>8. Check <b>Plots</b> and <b>Table</b> tabs for the results.</p>
<p>9. Click <b>restart</b> icon before running new analisys.",
),
),
shiny::tabPanel(
title = list(fontawesome::fa("people-group")),
shiny::br(),
shiny::HTML("<a href=\"mailto:[email protected]\">Arthur Ferreira, DSc</a>"),
shiny::HTML("<b> (Developer)</b>"),
shiny::br(),
shiny::br(),
shiny::HTML(
"<a href=\"mailto:[email protected]\">Gustavo Telles, MSc</a>; <a href=\"mailto:[email protected]\">Jessica Rio, MSc</a>; <a href=\"mailto:[email protected]\"> Maria Alice Pagnez, DSc</a>; <a href=\"mailto:[email protected]\">Leandro Nogueira, DSc</a>"
),
shiny::HTML("<b> (Contributors)</b>"),
shiny::br(),
shiny::br(),
shiny::HTML(
"<a href=\"https://www.unisuam.edu.br/programa-pos-graduacao-ciencias-da-reabilitacao\">PPGCR</a> | Programa de Pós-graduação em Ciências da Reabilitação, Centro Universitário Augusto Motta, Rio de Janeiro, RJ, Brazil"
),
shiny::HTML("<b> (Affiliation)</b>"),
shiny::br(),
shiny::br(),
shiny::HTML("<b>License</b>"),
shiny::HTML(
"This work is licensed under an <a rel=\"license\" data-spdx=\"Apache-2.0\" href=\"https://www.apache.org/licenses/LICENSE-2.0\">Apache License 2.0</a>."
),
shiny::br(),
shiny::HTML("<b>Cite as</b>"),
shiny::HTML(
"Ferreira, A.S. (2023). UsIA | Ultrasound Image Analysis (1.0.0). Zenodo. https://doi.org/10.5281/zenodo.10439718"
),
),
),
)
# Define server script
server <- function(input, output, session) {
# store plot click coords
roi_coords <-
shiny::reactiveValues(xy = data.frame(x = c(1, 1), y = c(1, 1)))
# observe plot click event ---------------------------------------------------------
shiny::observeEvent(input$roi_click, {
roi_coords$xy[2, ] <- round(c(input$roi_click$x, input$roi_click$y), digits = 0)
})
# free-hand drawing
vals = shiny::reactiveValues(x = NULL, y = NULL)
draw = shiny::reactiveVal(FALSE)
shiny::observeEvent(input$img_click, handlerExpr = {
temp <- draw()
draw(!temp)
if (!draw()) {
vals$x <- c(vals$x, NA)
vals$y <- c(vals$y, NA)
}
})
shiny::observeEvent(input$hover, {
if (draw()) {
vals$x <- c(vals$x, input$hover$x)
vals$y <- c(vals$y, input$hover$y)
}
})
shiny::observeEvent(input$reset, handlerExpr = {
vals$x <- NULL
vals$y <- NULL
})
# change to tab under event ---------------------------------------------------------
shiny::observeEvent(input[["buttAnalyze"]], {
shiny::updateTabsetPanel(inputId = "tabTrack",
selected = "track")
})
# enable/disable filter
shiny::observeEvent(input$FilterType, {
shinyjs::toggleState(id = "FilterSize", condition = input$FilterType != "none")
})
# upload video ---------------------------------------------------------
values <- shiny::reactiveValues(
upload_state = NULL
)
shiny::observeEvent(input$InputFile, {
values$upload_state <- 'uploaded'
})
shiny::observeEvent(input$restart, {
values$upload_state <- 'restart'
})
Video <- shiny::reactive({
if (is.null(values$upload_state)) {
return(NULL)
} else if (values$upload_state == 'uploaded') {
return(input[["InputFile"]][["datapath"]])
} else if (values$upload_state == 'restart') {
return(NULL)
}
})
# play uploaded video ---------------------------------------------------------
output[["videoraw"]] <- shiny::renderUI({
shiny::req(Video())
# Get video info such as width, height, format, duration and framerate
info <- av::av_media_info(Video())
# center ROI for the first time
roi_coords$xy[2, ] <- c(info$video$width / 2, info$video$height / 2)
# copy and rename file
file.copy(from = Video(),
to = file.path(dir.name, "rawvideo.mp4"))
# Splits a video file in a set of image files. Use format = "png" for losless images
av::av_video_images(
video = file.path(dir.name, "rawvideo.mp4"),
destdir = file.path(dir.name, "0 raw"),
format = "png",
fps = NULL
)
# copy raw files to edit folder
R.utils::copyDirectory(file.path(dir.name, "0 raw"), file.path(dir.name, "1 edited"))
# copy and rename file
file.copy(from = Video(),
to = file.path(dir.name, "editedvideo.mp4"))
# update max value of slider under event
shiny::updateSliderInput(
inputId = "framesEdit",
min = 1,
value = c(1, length(
list.files(file.path(dir.name, "0 raw"), pattern = ".png")
)),
max = length(list.files(
file.path(dir.name, "0 raw"), pattern = ".png"
))
)
# update max value of slider under event
shiny::updateSliderInput(
inputId = "imgEdit",
min = 1,
value = 1,
max = length(list.files(
file.path(dir.name, "0 raw"), pattern = ".png"
))
)
# show input video
tags$video(
width = "90%",
height = "90%",
controls = "",
tags$source(src = "rawvideo.mp4", type = "video/mp4")
)
})
# edit mp4 video using the sliderEdit input ---------------------------------------------------------
output[["videoedit"]] <- shiny::renderUI({
shiny::req(Video())
shiny::req(input$framesEdit)
# Get video info such as width, height, format, duration and framerate
info <- av::av_media_info(Video())
# generate mp4 video using the sliderEdit input
av::av_encode_video(
input = list.files(
file.path(dir.name, "0 raw"),
pattern = ".png",
full.names = TRUE
)[input$framesEdit[1]:input$framesEdit[2]],
output = file.path(dir.name, "editedvideo.mp4"),
framerate = info$video$framerate
)
# delete previous edit files
unlink(
list.files(
path = file.path(dir.name, "1 edited"),
recursive = TRUE,
include.dirs = TRUE,
full.names = TRUE,
pattern = "png"
)
)
# Splits a video file in a set of image files. Use format = "png" for losless images
av::av_video_images(
video = file.path(dir.name, "editedvideo.mp4"),
destdir = file.path(dir.name, "1 edited"),
format = "png",
fps = NULL
)
# update max value of slider under event
shiny::updateSliderInput(
inputId = "imgEdit",
min = 1,
value = 1,
max = length(list.files(
file.path(dir.name, "1 edited"), pattern = ".png"
))
)
# show video
tags$video(
width = "90%",
height = "90%",
controls = "",
tags$source(src = "editedvideo.mp4", type = "video/mp4")
)
})
# plot single frame of video imgEdit ---------------------------------------------------------
output[["plotMeasure"]] <- shiny::renderPlot({
shiny::req(Video())
shiny::req(input$framesEdit)
shiny::req(input$imgEdit)
# Get video info such as width, height, format, duration and framerate
info <- av::av_media_info(Video())
# show 1st frame
img <-
magick::image_read(
list.files(
path = file.path(dir.name, "1 edited"),
full.names = TRUE,
pattern = "png")[input$imgEdit]
)
# color palette (grayscale)
pal <- grDevices::gray(seq(
from = 0,
to = 1,
length.out = 256
), alpha = NULL)
par(mar = rep(0, 4), oma = rep(0, 4), omi = rep(0, 4), mai = rep(0, 4))
plot(
img,
xlim = c(0, info$video$width),
ylim = c(0, info$video$height),
asp = 1,
col = pal
)
# draw free-hand object
lines(
x = vals$x,
y = vals$y,
col = "red",
lty = "solid",
lwd = 2
)
}, height = function() {
(session$clientData$output_plotMeasure_width) * (0.6584)
})
# measurements of single frame of video imgEdit ---------------------------------------------------------
output[["tableMeasure"]] <- DT::renderDataTable({
shiny::req(Video())
shiny::req(input$framesEdit)
shiny::req(input$imgEdit)
shiny::req(input$imgScale)
# Get video info such as width, height, format, duration and framerate
info <- av::av_media_info(Video())
# show 1st frame
img <-
magick::image_read(
list.files(
path = file.path(dir.name, "1 edited"),
full.names = TRUE,
pattern = "png")[input$imgEdit]
)
# get separate channels
img_object <- as.integer(img[[1]])
img_object_R <- img_object[, , 1]
img_object_G <- img_object[, , 2]
img_object_B <- img_object[, , 3]
# flip image vertically
img_object_R <- img_object_R[nrow(img_object_R):1, ]
img_object_G <- img_object_G[nrow(img_object_G):1, ]
img_object_B <- img_object_B[nrow(img_object_B):1, ]
# create closed polygon
poly <- round(concaveman::concaveman(cbind(vals$x, vals$y), concavity = 1, length_threshold = 0), 0)
poly <- poly[complete.cases(poly), ]
# subset the image using polygon coordinates
img_object_R <- img_object_R[
min(poly[, 1]):max(poly[, 1]),
min(poly[, 2]):max(poly[, 2])
]
img_object_G <- img_object_G[
min(poly[, 1]):max(poly[, 1]),
min(poly[, 2]):max(poly[, 2])
]
img_object_B <- img_object_B[
min(poly[, 1]):max(poly[, 1]),
min(poly[, 2]):max(poly[, 2])
]
# custom functions
source("f_meas.R", local = TRUE)
data <- f_measurement(R = img_object_R, G = img_object_G, B = img_object_B, poly = poly)
contour <- data$contour
# draw actual ROI object
lines(
x = contour$x,
y = contour$y,
col = "red",
lty = "solid",
lwd = 2
)
# distance
distancia <- 0
# cross-sectional area
area <- distancia * distancia * pi
# show measurements
df_meas <- data.frame(
"File name" = input$InputFile[1],
"Frames (n)" = info$video$frames,
"Start - End (frames)" = paste0(input$framesEdit[1], " - ", input$framesEdit[2]),
"Video size (px)" = paste0(info$video$width, " x ", info$video$height),
"Current frame (n)" = input$imgEdit[1],
"Object size (px)" = max(poly[, 1] - min(poly[, 1])) * max(poly[, 2] - min(poly[, 2])),
"Distance (mm)" = round(distancia, digits = 2),
"Cross-sectional area (mm²)" = round(area, digits = 2),
"Threshold (Otsu)" = data$threshold,
"Echogenicity, B&W (%)" = round(data$ecogenicidade_bw, digits = 2),
"Echogenicity, gray (%)" = round(data$ecogenicidade_gray, digits = 2)
)
df_meas <- t(df_meas)
labels <-
c(
"File name",
"Frames (n)",
"Start - End (frames)",
"Video size (px)",
"Current frame (n)",
"Object size (px)",
"Distance (mm)",
"Cross-sectional area (mm²)",
"Threshold (Otsu)",
"Echogenicity, B&W (%)",
"Echogenicity, gray (%)"
)
rownames(df_meas) <-
labels
# show DT table with buttons
DT::datatable(
df_meas,
rownames = TRUE,
colnames = rep("", ncol(df_meas)),
extensions = c("Buttons", "FixedColumns"),
options = list(
dom = "B",
ordering = F,
buttons = list(
list(extend = "copy",
text = "Copy"),
list(extend = "csv",
text = "CSV"),
list(extend = "excel",
text = "Excel"),
list(extend = "pdf",
text = "PDF")
),
fixedColumns = TRUE,
pageLength = length(labels),
autoWidth = TRUE,
columnDefs = list(list(className = 'dt-center', targets = "_all"))
)
)
})
# show PNG file of 1st frame ---------------------------------------------------------
output[["plotROI"]] <- shiny::renderPlot({
shiny::req(Video())
shiny::req(input$framesEdit)
# Get video info such as width, height, format, duration and framerate
info <- av::av_media_info(Video())
# show 1st frame
img <-
magick::image_read(
list.files(
path = file.path(dir.name, "1 edited"),
full.names = TRUE,
pattern = "png")[1]
)
# color palette (grayscale)
pal <- grDevices::gray(seq(
from = 0,
to = 1,
length.out = 256
), alpha = NULL)
par(mar = rep(0, 4), oma = rep(0, 4), omi = rep(0, 4), mai = rep(0, 4))
plot(
img,
xlim = c(0, info$video$width),
ylim = c(0, info$video$height),
asp = 1,
col = pal
)
# custom functions
round_2_odd <- function(x) {
2 * floor(x / 2) + 1
}
# draw object rectangle
rect(
xleft = roi_coords$xy[2, 1] - floor(input$KernelSizeTrack / 2),
ybottom = roi_coords$xy[2, 2] - floor(input$KernelSizeTrack / 2),
xright = roi_coords$xy[2, 1] + floor(input$KernelSizeTrack / 2),
ytop = roi_coords$xy[2, 2] + floor(input$KernelSizeTrack / 2),
col = "transparent",
border = "red",
lty = "solid",
lwd = 2
)
roi <-
round_2_odd(input$KernelSizeTrack * (1 + as.numeric(input$Overlap) / 100)) # odd numbers only
# draw ROI rectangle
rect(
xleft = roi_coords$xy[2, 1] - floor(roi / 2),
ybottom = roi_coords$xy[2, 2] - floor(roi / 2),
xright = roi_coords$xy[2, 1] + floor(roi / 2),
ytop = roi_coords$xy[2, 2] + floor(roi / 2),
col = "transparent",
border = "yellow",
lty = "solid",
lwd = 2
)
# show coordinates of ROI
text(
x = roi_coords$xy[2, 1],
y = roi_coords$xy[2, 2],
paste0(
"x=",
round(roi_coords$xy[2, 1], 0),
"\n",
"y=",
round(roi_coords$xy[2, 2], 0)
),
col = "red"
)
}, height = function() {
(session$clientData$output_plotROI_width) * (0.6584)
})
# process, play and export video ---------------------------------------------------------
shiny::observeEvent(input[["buttAnalyze"]], {
shiny::req(Video())
# Get video info such as width, height, format, duration and framerate
info <- av::av_media_info(Video())
# Capture the result of us_track function call
us_track(
center.ini <-
list(x = roi_coords$xy[2, 1], y = roi_coords$xy[2, 2]),
inputfile = file.path(dir.name, "editedvideo.mp4"),
filtertype = input$FilterType,
filtersize = input$FilterSize,
overlap = input$Overlap,
jump = input$Jump,
kernel = input$KernelSizeTrack
)
# draw trajectory on images
path <-
read.csv(file.path(dir.name, "CSV", "trajectory_measured.csv"))
for (i in 1:length(list.files(file.path(dir.name, "8 output")))) {
# read image from file
img <- png::readPNG(file.path(dir.name, "8 output", paste0("image_", sprintf("%06d", i), ".png")))
img <- grDevices::as.raster(img[, , 1:3])
# create a ggplot object with the image in background and trajectory as data points
par(mar = rep(0, 4), oma = rep(0, 4), omi = rep(0, 4), mai = rep(0, 4))
ggplot2::ggplot() +
ggplot2::annotation_raster(
img,
xmin = 0,
xmax = info$video$width,
ymin = 0,
ymax = info$video$height,
interpolate = TRUE
) +
ggplot2::geom_point(
data = path[1:i,],
ggplot2::aes(x = X, y = Y),
colour = "red",
size = 100
) +
ggplot2::scale_x_continuous(limits = c(0, info$video$width),
expand = c(0, 0)) +
ggplot2::scale_y_continuous(limits = c(0, info$video$height),
expand = c(0, 0)) +
ggplot2::coord_fixed() +
ggplot2::theme_void()
# save ggplot as png
ggplot2::ggsave(
filename = file.path(dir.name, "8 output", paste0("image_", sprintf("%06d", i), ".png")),
width = info$video$width,
height = info$video$height,
units = "px",
dpi = 1,
type = "cairo",
limitsize = FALSE
)
}
# build mp4 video using av video package from out.dir files
av::av_encode_video(
input = list.files(
file.path(dir.name, "8 output"),
pattern = ".png",
full.names = TRUE
),
output = file.path(dir.name, "outputvideo.mp4"),
framerate = info$video$framerate
)
})
# show MP4 video of output file
output[["videooutput"]] <- shiny::renderUI({
shiny::req(Video())
# Get video info such as width, height, format, duration and framerate
info <- av::av_media_info(Video())
# show video
tags$video(
width = "90%",
height = "90%",
controls = "",
tags$source(src = "outputvideo.mp4", type = "video/mp4")
)
})
df <-
shiny::reactive(if (file.exists(file.path(
dir.name, "CSV", "max_cross_correlation.csv"
)) &
file.exists(file.path(dir.name, "CSV", "displacement.csv"))) {
info <- av::av_media_info(Video())
data.frame(
"File name" = input$InputFile[1],
"Frames (n)" = info$video$frames,
"Start - End (frames)" = paste0(input$framesEdit[1], " - ", input$framesEdit[2]),
"Video size (px)" = paste0(info$video$width, " x ", info$video$height),
"X0 (px)" = round(roi_coords$xy[2, 1], 0),
"Y0 (px)" = round(roi_coords$xy[2, 2], 0),
"Object size (px)" = input$KernelSizeTrack,
"Filter type" = input$FilterType,
"Filter size (px)" = input$FilterSize,
"Overlap (%)" = input$Overlap,
"Jump (frames)" = input$Jump,
"Displacement, total (px)" = round(sum(read.csv(
file.path(dir.name, "CSV", "displacement.csv")
)[[1]], na.rm = TRUE), 0),
"Displacement, mean (px)" = round(mean(read.csv(
file.path(dir.name, "CSV", "displacement.csv")
)[[1]], na.rm = TRUE), 0),
"Speed, mean (px/frame)" = round(mean(abs(
diff(read.csv(
file.path(dir.name, "CSV", "displacement.csv")
)[[1]], differences = 1)
), na.rm = TRUE), 3),
"Speed, max (px/frame)" = round(max(abs(
diff(read.csv(
file.path(dir.name, "CSV", "displacement.csv")
)[[1]], differences = 1)
), na.rm = TRUE), 3),
"Cross-correlation, max" = round(max(read.csv(
file.path(dir.name, "CSV", "max_cross_correlation.csv")
)[[1]], na.rm = TRUE), 3),
"Cross-correlation, mean" = round(mean(read.csv(
file.path(dir.name, "CSV", "max_cross_correlation.csv")
)[[1]], na.rm = TRUE), 3),
"Cross-correlation, min" = round(min(read.csv(
file.path(dir.name, "CSV", "max_cross_correlation.csv")
)[[1]], na.rm = TRUE), 3)
)
} else {
info <- av::av_media_info(Video())
data.frame(
"File name" = input$InputFile[1],
"Frames (n)" = info$video$frames,
"Start - End (frames)" = paste0(input$framesEdit[1], " - ", input$framesEdit[2]),
"Video size (px)" = paste0(info$video$width, " x ", info$video$height),
"X0 (px)" = round(roi_coords$xy[2, 1], 0),
"Y0 (px)" = round(roi_coords$xy[2, 2], 0),
"Object size (px)" = input$KernelSizeTrack,
"Filter type" = input$FilterType,
"Filter size (px)" = input$FilterSize,
"Overlap (%)" = input$Overlap,
"Jump (frames)" = input$Jump,
"Displacement, total (px)" = NA,
"Displacement, mean (px)" = NA,
"Speed, mean (px/frame)" = NA,
"Speed, max (px/frame)" = NA,
"Cross-correlation, max" = NA,