Use NerfUtils.jl (#16)

.gitignore

@@ -1,5 +1,5 @@
-Manifest.toml
 LocalPreferences.toml
 test/image.png
 *.png
 docs/build/
+Manifest.toml

Project.toml

@@ -18,16 +18,32 @@ JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
 JpegTurbo = "b835a17e-a41a-41e7-81f0-2f016b05efe0"
 KernelAbstractions = "63c18a36-062a-441e-b654-da1e3ab1ce7c"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+NerfUtils = "99c1d5ce-7c61-4a25-a107-a5ade2e2a8e4"
 Preferences = "21216c6a-2e73-6563-6e65-726566657250"
 Quaternions = "94ee1d12-ae83-5a48-8b1c-48b8ff168ae0"
-Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
 Rotations = "6038ab10-8711-5258-84ad-4b1120ba62dc"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [compat]
-AMDGPU = "0.5"
-CUDA = "4.4"
+AMDGPU = "0.6"
+Adapt = "3.6"
+BSON = "0.3"
+BenchmarkTools = "1.3.2"
+CUDA = "5"
+ChainRulesCore = "1.16"
+FileIO = "1.16"
+ImageCore = "0.10"
+ImageMagick = "1.3"
+ImageTransformations = "0.10"
+JSON = "0.21"
+JpegTurbo = "0.1"
 KernelAbstractions = "0.9"
-Zygote = "0.6.55"
+NerfUtils = "0.1"
+Preferences = "1.4"
+Quaternions = "0.7"
+Rotations = "1.6"
+StaticArrays = "1.6"
+Zygote = "0.6"
+julia = "1.9"

benchmark/pipeline.jl

@@ -1,4 +1,5 @@
 using Nerf
+using NerfUtils
 using LinearAlgebra
 using StaticArrays
 
@@ -28,18 +29,26 @@ function benchmark()
 
     Core.println("Trainer benchmark")
 
+    GC.gc(true)
+    GC.gc(false)
     @time trainer_benchmark(trainer, 10)
+    GC.gc(true)
+    GC.gc(false)
     @time trainer_benchmark(trainer, 1000)
 
-    camera = Nerf.Camera(MMatrix{3, 4, Float32}(I), dataset.intrinsics)
-    Nerf.set_projection!(camera, Nerf.get_pose(dataset, 1)...)
+    camera = Camera(MMatrix{3, 4, Float32}(I), dataset.intrinsics)
+    NerfUtils.set_projection!(camera, Nerf.get_pose(dataset, 1)...)
     renderer = Nerf.Renderer(Backend, camera, trainer.bbox, trainer.cone)
 
     Core.println("Renderer benchmark")
 
+    GC.gc(true)
+    GC.gc(false)
     @time render_benchmark(renderer, trainer, 2)
+    GC.gc(true)
+    GC.gc(false)
     @time render_benchmark(renderer, trainer, 10)
 
-    nothing
+    return
 end
 benchmark()

src/Nerf.jl

@@ -10,13 +10,16 @@ using JSON
 using KernelAbstractions
 using KernelAbstractions: @atomic, unsafe_free!
 using LinearAlgebra
+using NerfUtils
 using Preferences
 using Quaternions
 using Rotations
 using StaticArrays
 using Statistics
 using Zygote
 
+import NerfUtils as NU
+
 struct Literal{T} end
 Base.:(*)(x, ::Type{Literal{T}}) where {T} = T(x)
 const u32 = Literal{UInt32}
@@ -75,9 +78,7 @@ include("bbox.jl")
 include("data/dataset.jl")
 include("ray.jl")
 include("acceleration/occupancy.jl")
-include("encoding/grid.jl")
 include("encoding/spherical_harmonics.jl")
-include("nn/nn.jl")
 include("sampler.jl")
 include("loss.jl")
 include("trainer.jl")
@@ -105,10 +106,10 @@ function main()
         loss = step!(trainer)
         @show i, loss
 
-        i % 1000 == 0 || continue
+        i % 500 == 0 || continue
 
         pose_idx = clamp(round(Int, rand() * length(dataset)), 1, length(dataset))
-        set_projection!(camera, get_pose(dataset, pose_idx)...)
+        NU.set_projection!(camera, get_pose(dataset, pose_idx)...)
         render!(renderer, trainer.occupancy, trainer.bbox) do points, directions
             model(points, directions)
         end

src/data/images.jl

@@ -50,7 +50,7 @@ end
 
     # TODO parametrize Images type on the number of channels
     a = if size(images.data, 1) == 4
-        Float32(images.data[4, pixel[1], pixel[2], image_idx]) * scale
+        @inbounds Float32(images.data[4, pixel[1], pixel[2], image_idx]) * scale
     else
         1f0
     end

src/data/intrinsics.jl

@@ -1,21 +1,9 @@
-struct CameraIntrinsics{D}
-    distortion::SVector{4, Float32}
-    focal::SVector{2, Float32}
-    principal::SVector{2, Float32}
-    resolution::SVector{2, UInt32}
-
-    function CameraIntrinsics(distortion, focal, principal, resolution)
-        has_distortion = !iszero(distortion)
-        new{has_distortion}(distortion, focal, principal, resolution)
-    end
-end
-
 """
     CameraIntrinsics(config)
 
 Construct CameraIntrinsics from a config file.
 """
-function CameraIntrinsics(config)
+function NerfUtils.CameraIntrinsics(config)
     w, h = config["w"], config["h"]
     resolution = SVector{2, UInt32}(w, h)
 
@@ -37,26 +25,10 @@ end
 
 Construct intrinsics for synthetic dataset.
 """
-function CameraIntrinsics(width, height, fov)
+function NerfUtils.CameraIntrinsics(width, height, fov)
     resolution = SVector{2, UInt32}(width, height)
     principal = SVector{2, Float32}(0.5f0, 0.5f0)
-    focal = fov2focal(resolution, rad2deg(fov))
+    focal = NerfUtils.fov2focal(resolution, rad2deg(fov))
     distortion = zeros(SVector{4, Float32})
     CameraIntrinsics(distortion, focal, principal, resolution)
 end
-
-# Copy constructor.
-function CameraIntrinsics(
-    c::CameraIntrinsics; distortion=c.distortion, focal=c.focal,
-    principal=c.principal, resolution=c.resolution,
-)
-    CameraIntrinsics(distortion, focal, principal, resolution)
-end
-
-function fov2focal(resolution, degrees::Float32)
-    0.5f0 * resolution / tan(0.5f0 * deg2rad(degrees))
-end
-
-function focal2fov(resolution, focal_length)
-    2f0 * rad2deg(atan(resolution / (focal_length * 2f0)))
-end