In MilesMcBain/r2vr: Compose and Serve WebVR Scenes

  knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.height = 3,
  fig.width = 7
  )
require(knitr)

Annotate 2D Virtual Reality Images by Creating an Interactive WebVR scene

r2vr has been extended to be able to help train users to annotate virtual reality images more accurately. The 2D Training will randomly select 3 images from a pool of images. Users are able to annotate selected markers (for each image) as either C or N to classify the bounded region as either containing mostly Coral or Not Coral respectively. The user's annotations are then compared to a gold standard, which are the correct annotations for the corresponding fixed points in which the user annotated. The user will then be able to receive visual feedback with markers changing to green or red depending on if they annotated the marker correctly or incorrectly respectively.

Case Study: Coral Cover

library(r2vr)
IPv4_ADDRESS <- find_IP() # Note: If not on Windows, enter IP directly

## TODO: SET full name here
# set_user("Firstname-Lastname") # default to be overridden
set_user("Jon-Peppinck")

## OPTIONAL: '?set_marker_and_props' shows configuration options
# i.e. Number of markers and size of markers, but keep "2d"
# set_marker_and_props("2d") # 
set_marker_and_props("2d", 10, "small")


## OPTIONAL: '?set_colors'
# e.g. set_colors(coral = "#FFFF00", not_coral = "#FF00FF", evaluation_selection = "#0000FF")
set_colors()

## Note: images are 4000x3000 (px) i.e. 0 <= x <= 4000, 0 <= y <= 3000
# Where (0, 0) is top left corner, (4000, 3000) is bottom right corner
# 49001074001.jpeg
img1Points = list(
  list(id = 1, x = 3203, y = 173, isCoral = 0), # Not Coral - sand
  list(id = 2, x = 2335, y = 2755, isCoral = 0), # Not Coral - sand
  list(id = 3, x = 2291, y = 1086, isCoral = 0), # Not Coral - sand
  list(id = 4, x = 1013, y = 399 , isCoral = 1), # Coral - Hard corals
  list(id = 5, x = 1704, y = 570, isCoral = 1), # Coral - Hard corals
  list(id = 6, x = 2466, y = 1274, isCoral = 1), # Coral - Hard corals
  list(id = 7, x = 3768, y = 1413, isCoral = 1), # Coral - Hard corals
  list(id = 8, x =  1376, y = 1458, isCoral = 1), # Coral - Hard corals
  list(id = 9, x = 524, y = 1635, isCoral = 1), # Coral - Hard corals
  list(id = 10, x = 1448, y = 2156, isCoral = 1) # Coral - Hard corals
)
# 49002256001.jpeg
img2Points = list(
  list(id = 1, x = 3498, y = 354, isCoral = 0), # Not Coral - Algae
  list(id = 2, x = 234, y = 864, isCoral = 0), # Not Coral - Algae
  list(id = 3, x = 1132, y = 2709, isCoral = 0), # Not Coral - sand
  list(id = 4, x = 2386, y = 299, isCoral = 0), # Not Coral - sand
  list(id = 5, x = 1302, y = 442, isCoral = 0), # Not Coral - sand
  list(id = 6, x = 2773, y = 472, isCoral = 0), # Not Coral - sand
  list(id = 7, x = 318, y = 2503, isCoral = 0), # Not Coral - sand
  list(id = 8, x = 3722, y = 683, isCoral = 0), # Not Coral - sand
  list(id = 9, x = 1501, y = 1346, isCoral = 0), # Not Coral - sand
  list(id = 10, x = 3673, y = 2605, isCoral = 1) # Coral - Hard corals
)
# 51010026001.jpeg
img3Points = list(
  list(id = 1, x = 330, y = 2847, isCoral = 0), # Not Coral - Algae
  list(id = 2, x = 702, y = 1144, isCoral = 0), # Not Coral - Algae
  list(id = 3, x = 3737, y = 2312, isCoral = 0), # Not Coral - Algae
  list(id = 4, x = 2628, y = 343, isCoral = 0), # Not Coral - sand
  list(id = 5, x = 2043, y = 557, isCoral = 0), # Not Coral - sand
  list(id = 6, x = 3510, y = 966, isCoral = 0), # Not Coral - sand
  list(id = 7, x = 1413, y = 2503, isCoral = 0), # Not Coral - sand
  list(id = 8, x = 1541, y = 186, isCoral = 0), # Not Coral - sand
  list(id = 9, x = 2030, y = 2521, isCoral = 0), # Not Coral - sand
  list(id = 10, x = 3363, y = 2745, isCoral = 1) # Coral - Hard corals
)

R2VR_CDN <- "https://cdn.jsdelivr.net/gh/ACEMS/r2vr@experiment" # NOTE: Subject to change

R2VR_2D_IMAGES <- paste0(R2VR_CDN, "/inst/ext/images/2d/")

# TODO: Select images (4000x3000px)
# NOTE: If have other local images on PC can change img_paths to be a vector of relative file location for the current working directory.
# NOTE: can have more than 3 images in img_paths
img_paths <- paste0(
  R2VR_2D_IMAGES,
  c("49001074001.jpeg",
    "49002256001.jpeg",
    "51010026001.jpeg")
)

img_paths_and_points <- list(
  # 2D image paths  4000x3000
  list(img = img_paths[1], img_points = img1Points),
  list(img = img_paths[2], img_points = img2Points),
  list(img = img_paths[3], img_points = img3Points)
)

# Select 3 random images and corresponding points from list
set_random_images(img_paths_and_points)

animals <- shared_setup_scene("2d", "training") # DON'T CHANGE

COMMANDS - 2D TRAINING

start()
fixed_markers()
go_to()
go_to()
check(1)
check(2)
check(3)
end()
training_2d.df <- read("https://r2vr.herokuapp.com/api/2d/training")
rm(list=ls())