From 37649addf21623926af8eb5964796876eb6bb66c Mon Sep 17 00:00:00 2001 From: TheNumbat Date: Tue, 23 Feb 2021 13:08:07 -0500 Subject: [PATCH] mention cbox lambertian in path tracing task --- docs/pathtracer/materials.md | 2 +- docs/pathtracer/path_tracing.md | 4 +- media/cbox_lambertian.dae | 544 ++++++++++++++++++++++++++++++++ 3 files changed, 547 insertions(+), 3 deletions(-) create mode 100644 media/cbox_lambertian.dae diff --git a/docs/pathtracer/materials.md b/docs/pathtracer/materials.md index a289180..2708a52 100644 --- a/docs/pathtracer/materials.md +++ b/docs/pathtracer/materials.md @@ -67,7 +67,7 @@ Alternatively, you may compute using We described the BRDF for perfect specular reflection in class, however we did not discuss the distribution function for transmitted light. Since refraction "spreads" or "condenses" a beam, unlike perfect reflection, the radiance along the ray changes due to a refraction event. In your assignment you should use Snell's Law to compute the direction of refraction rays, and use the following distribution function to compute the radiance of transmitted rays. We refer you guys to Pharr, Jakob, and and Humphries's book [Physically Based Rendering](http://www.pbr-book.org/) for a derivation based on Snell's Law and the relation . (But you are more than welcome to attempt a derivation on your own!) -When you are done, you will be able to render images like these: +When you are done, you will be able to render images like this one, the Cornell Box with a metal and glass sphere (`cbox.dae`):
diff --git a/docs/pathtracer/path_tracing.md b/docs/pathtracer/path_tracing.md index a38158b..3e08907 100644 --- a/docs/pathtracer/path_tracing.md +++ b/docs/pathtracer/path_tracing.md @@ -35,11 +35,11 @@ Note: --- -After correctly implementing path tracing, your renderer should be able to make a beautifully lit picture of the Cornell Box. Below is the rendering result of 1024 sample per pixel. +After correctly implementing path tracing, your renderer should be able to make a beautifully lit picture of the Cornell Box with Lambertian spheres (`cbox_lambertian.dae`). Below is a render using 1024 samples per pixel: ![cornell_lambertian](new_results/lambertian.png) -Note the time-quality tradeoff here. With these commandline arguments, your path tracer will be running with 8 worker threads at a sample rate of 1024 camera rays per pixel, with a max ray depth of 4. This will produce an image with relatively high quality but will take quite some time to render. Rendering a high quality image will take a very long time as indicated by the image sequence below, so start testing your path tracer early! Below are the result and runtime of rendering cornell box with different sample per pixel at 640 by 430 on Macbook Pro(3.1 GHz Dual-Core Intel Core i5). +Note the time-quality tradeoff here. With these arguments, your path tracer will be running at a sample rate of 1024 camera rays per pixel, with a max ray depth of 4. This will produce an image with relatively high quality but will take quite some time to render. Rendering a high quality image will take a very long time as indicated by the image sequence below, so start testing your path tracer early! Below are the result and runtime of rendering cornell box with different sample per pixel at 640 by 430 on Macbook Pro(3.1 GHz Dual-Core Intel Core i5). ![spheres](new_results/timing.png) diff --git a/media/cbox_lambertian.dae b/media/cbox_lambertian.dae new file mode 100644 index 0000000..2ee8f58 --- /dev/null +++ b/media/cbox_lambertian.dae @@ -0,0 +1,544 @@ + + + + + Assimp + Assimp Exporter + + 2021-02-23T13:02:26 + 2021-02-23T13:02:26 + + Y_UP + + + + + + + 121.28508 + 1.7778001 + 0 + 1 + + + + + + + + + 121.28449 + 1.7777778 + 0 + 1 + + + + + + + + + + 10 10 10 + 0.25 + 0.25 + 10 + + + + + + + + + + + + + 1 1 1 1 + + + 0.7474227 0.26583591 0.26583591 1 + + + 1 + + + 1 1 1 1 + + + 1 1 1 1 + + + 1.2 + + + + + + + + + + + 1 1 1 1 + + + 0.29386759 0.29386783 0.81443298 1 + + + 1 + + + 1 1 1 1 + + + 1 1 1 1 + + + 1.2 + + + + + + + + + + + 1 1 1 1 + + + 1 1 1 1 + + + 1 + + + 1 1 1 1 + + + 1 1 1 1 + + + 1.2 + + + + + + + + + + + 1 1 1 1 + + + 1 1 1 1 + + + 1 + + + 1 1 1 1 + + + 1 1 1 1 + + + 1.2 + + + + + + + + + + + 1 1 1 1 + + + 1 1 1 1 + + + 1 + + + 1 1 1 1 + + + 1 1 1 1 + + + 1.2 + + + + + + + + + + + 1 1 1 1 + + + 1 1 1 1 + + + 0.2 0.2 0.2 1 + + + 1 + + + 1 1 1 1 + + + 1 1 1 1 + + + 1.2 + + + + + + + + + + + 1 1 1 1 + + + 1 1 1 1 + + + 0.2 0.2 0.2 1 + + + 1 + + + 1 1 1 1 + + + 1 1 1 1 + + + 1.5 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 0.5 0 -0.5 -0.5 0 -0.5 -0.5 0 0.5 0.5 0 0.5 + + + + + + + + + + + + + + 3 3 +

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