Introduction
Read and display a PFM image
PFM (Portable Float Map) is a simple format for
storing Gray or RGB colour data. Pixels are stored as 32-bit floating
point values in a simple array format.
Load and display a (PFM) image.
Apply tone-mapping to the image and adjust the gamma correction prior to display.
filename <- system.file("image/rstats.pfm.bz2", package = "picohdr")
im <- read_pfm(filename)
dim(im)
#> [1] 280 420 3
im |>
tm_reinhard() |>
adj_gamma() |>
plot()
Read and display an EXR image
OpenEXR images are a more complex HDR image container.
Pixel types may be 16-bit floats, 32-bit floats or 32-bit unsigned
integers.
Images can contain any number of channels with arbitrary names - this includes data that isn’t related to the colour of the display e.g. image depth, texture coordinates.
The actual image data may be stored as scanlines, tiles or deep images in single- or multi-part formats.
Currently, this package only supports reading single-part
scanline images which are using NONE,
ZIP or ZIPS compression.
The steps included below:
- Load an EXR image as an array
- Show the names of the channels in this array
- Select the RGB channels from the array and plot them (after applying tone-mapping and gamma correction)
- Plot some other channels in the image
- Display the metainformation about an EXR image using
exr_info()
library(picohdr)
# EXR file of meta-information about the rendered scene
filename <- system.file("image/rstats.exr", package = "picohdr")
# Load all images
images <- read_exr(filename)
dim(im)
#> [1] 280 420 3
# Channel names. EXR format wants channels arranged alphabetically
dimnames(images)[[3]]
#> [1] "Albedo.B" "Albedo.G" "Albedo.R"
#> [4] "B" "G" "N.X"
#> [7] "N.Y" "N.Z" "Ns.X"
#> [10] "Ns.Y" "Ns.Z" "P.X"
#> [13] "P.Y" "P.Z" "R"
#> [16] "RelativeVariance.B" "RelativeVariance.G" "RelativeVariance.R"
#> [19] "Variance.B" "Variance.G" "Variance.R"
#> [22] "dzdx" "dzdy" "u"
#> [25] "v"
# Extract RGB channels. Tone-map. Adjust gamma.
images[,,c('R', 'G', 'B')] |>
tm_reinhard() |>
adj_gamma() |>
plot()
Display a non-colour channel
This EXR file includes information about the surface derivative at
each point in the image in the dzdx channel.
This value may be negative or positive, so we will map the values into the standard range [0, 1] so it can be visualised.
# Rescale the derivative channel to the range [0,1] and display
images[,,'dzdx'] |>
adj_rescale(0, 1) |>
plot()
EXR metadata
Meta-information about the contents of an EXR file can be extracted for all EXR image types.
exr_info(filename)
#> $version
#> $version$number
#> [1] 2
#>
#> $version$single_tile
#> [1] FALSE
#>
#> $version$long_name
#> [1] FALSE
#>
#> $version$non_image
#> [1] FALSE
#>
#> $version$multipart
#> [1] FALSE
#>
#> $version$desc
#> [1] "single-part scanline"
#>
#>
#> $channels
#> name type pLinear xSampling ySampling
#> 1 Albedo.B half 0 1 1
#> 2 Albedo.G half 0 1 1
#> 3 Albedo.R half 0 1 1
#> 4 B half 0 1 1
#> 5 G half 0 1 1
#> 6 N.X half 0 1 1
#> 7 N.Y half 0 1 1
#> 8 N.Z half 0 1 1
#> 9 Ns.X half 0 1 1
#> 10 Ns.Y half 0 1 1
#> 11 Ns.Z half 0 1 1
#> 12 P.X half 0 1 1
#> 13 P.Y half 0 1 1
#> 14 P.Z half 0 1 1
#> 15 R half 0 1 1
#> 16 RelativeVariance.B half 0 1 1
#> 17 RelativeVariance.G half 0 1 1
#> 18 RelativeVariance.R half 0 1 1
#> 19 Variance.B half 0 1 1
#> 20 Variance.G half 0 1 1
#> 21 Variance.R half 0 1 1
#> 22 dzdx half 0 1 1
#> 23 dzdy half 0 1 1
#> 24 u half 0 1 1
#> 25 v half 0 1 1
#>
#> $compression
#> [1] "ZIP"
#>
#> $dataWindow
#> [1] 0 0 359 269
#>
#> $displayWindow
#> [1] 0 0 359 269
#>
#> $lineOrder
#> [1] "increasing"
#>
#> $pixelAspectRatio
#> [1] 1
#>
#> $renderTimeSeconds
#> [1] 43.84048
#>
#> $samplesPerPixel
#> [1] 1024
#>
#> $screenWindowCenter
#> [1] 0 0
#>
#> $screenWindowWidth
#> [1] 1
#>
#> $worldToCamera
#> [,1] [,2] [,3] [,4]
#> [1,] 0.7657048 -0.6431921 -1.233992e-09 -1.2251276
#> [2,] -0.2218857 -0.2641496 9.386115e-01 0.1672952
#> [3,] -0.6037076 -0.7186995 -3.449758e-01 14.9489479
#> [4,] 0.0000000 0.0000000 0.000000e+00 1.0000000
#>
#> $worldToNDC
#> [,1] [,2] [,3] [,4]
#> [1,] 4.5627465 -4.4456143 -0.1724879 -0.3088861
#> [2,] -1.7115160 -2.0375190 5.7906065 8.5373173
#> [3,] -0.6037106 -0.7187030 -0.3449775 14.9440222
#> [4,] -0.6037076 -0.7186995 -0.3449758 14.9489479
#>
#> $chunk_offsets
#> [1] 1202 79967 158319 238640 338013 456525 582637 720330 863085
#> [10] 1000992 1127091 1242213 1339482 1428107 1514095 1597924 1680690EXR Implementation Notes
The code for handling EXR images is mostly written in base R with the exception of a core compression/decompression component which is written in C:
The ZIP compression mode applies a predictor and de-interleaves bytes. The byte predictor and interleaving can be in R but is 20x faster in C.
EXR support is for a subset of images which:
- consist of a single-part scanline image.
- use the
NONE,ZIPorZIPScompression
This package does not support the following EXR features:
- multi-part images
- deep images
- tiled images
If you would like support for these features please file an issue on GitHub. A link to a free/openly-licensed image containing your requested features would be appreciated.