{ "cells": [ { "cell_type": "markdown", "id": "24a98647", "metadata": {}, "source": [ "## Checking consistency of acceleration structures\n", "\n", "This test checks consistencies between different acceleration structures. We render the images with `renderer::raycast` with different accelleration structures for various scenes, and compute differences among them. If the implementations are correct, all difference images should be blank because ray-triangle intersection is a deterministic process." ] }, { "cell_type": "code", "execution_count": 1, "id": "f1a0f492", "metadata": { "execution": { "iopub.execute_input": "2021-10-22T11:34:39.984752Z", "iopub.status.busy": "2021-10-22T11:34:39.984092Z", "iopub.status.idle": "2021-10-22T11:34:40.081758Z", "shell.execute_reply": "2021-10-22T11:34:40.082192Z" } }, "outputs": [], "source": [ "import lmenv\n", "env = lmenv.load('.lmenv')" ] }, { "cell_type": "code", "execution_count": 2, "id": "b4dcd3ce", "metadata": { "execution": { "iopub.execute_input": "2021-10-22T11:34:40.085353Z", "iopub.status.busy": "2021-10-22T11:34:40.084660Z", "iopub.status.idle": "2021-10-22T11:34:40.592505Z", "shell.execute_reply": "2021-10-22T11:34:40.592057Z" } }, "outputs": [], "source": [ "import os\n", "import imageio\n", "import pandas as pd\n", "import numpy as np\n", "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", "import lmscene\n", "import lightmetrica as lm" ] }, { "cell_type": "code", "execution_count": 3, "id": "f3a17528", "metadata": { "execution": { "iopub.execute_input": "2021-10-22T11:34:40.597570Z", "iopub.status.busy": "2021-10-22T11:34:40.596471Z", "iopub.status.idle": "2021-10-22T11:34:40.603774Z", "shell.execute_reply": "2021-10-22T11:34:40.603277Z" } }, "outputs": [], "source": [ "%load_ext lightmetrica_jupyter" ] }, { "cell_type": "code", "execution_count": 4, "id": "ece83060", "metadata": { "code_folding": [ 0 ], "execution": { "iopub.execute_input": "2021-10-22T11:34:40.610904Z", "iopub.status.busy": "2021-10-22T11:34:40.605823Z", "iopub.status.idle": "2021-10-22T11:34:40.614618Z", "shell.execute_reply": "2021-10-22T11:34:40.615013Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[I|0.000] Lightmetrica -- Version 3.0.0 (rev. 70601db) Linux x64\n", "[I|0.000] Loading plugin [name='accel_nanort']\n", "[I|0.001] .. Successfully loaded [name='accel_nanort']\n", "[I|0.001] Loading plugin [name='accel_embree']\n", "[I|0.002] .. Successfully loaded [name='accel_embree']\n" ] } ], "source": [ "# Initialize Lightmetrica\n", "lm.init()\n", "lm.log.init('jupyter')\n", "lm.progress.init('jupyter')\n", "lm.info()\n", "lm.comp.load_plugin(os.path.join(env.bin_path, 'accel_nanort'))\n", "lm.comp.load_plugin(os.path.join(env.bin_path, 'accel_embree'))" ] }, { "cell_type": "markdown", "id": "4bd6bbe7", "metadata": {}, "source": [ "### Difference images (pixelwised RMSE)\n", "\n", "Correct if the difference images are blank." ] }, { "cell_type": "code", "execution_count": 5, "id": "2d00d9e2", "metadata": { "code_folding": [ 0 ], "execution": { "iopub.execute_input": "2021-10-22T11:34:40.620171Z", "iopub.status.busy": "2021-10-22T11:34:40.619682Z", "iopub.status.idle": "2021-10-22T11:34:40.623029Z", "shell.execute_reply": "2021-10-22T11:34:40.622604Z" } }, "outputs": [], "source": [ "# Function to build and render the image\n", "def build_and_render(scene, accel_name):\n", " accel = lm.load_accel('accel', accel_name)\n", " scene.set_accel(accel.loc())\n", " scene.build()\n", " film = lm.load_film('film_output', 'bitmap', w=1920, h=1080)\n", " renderer = lm.load_renderer('renderer', 'raycast', scene=scene, output=film)\n", " renderer.render()\n", " return np.copy(film.buffer())" ] }, { "cell_type": "code", "execution_count": 6, "id": "fa7de8f5", "metadata": { "code_folding": [], "execution": { "iopub.execute_input": "2021-10-22T11:34:40.627137Z", "iopub.status.busy": "2021-10-22T11:34:40.626625Z", "iopub.status.idle": "2021-10-22T11:34:40.629529Z", "shell.execute_reply": "2021-10-22T11:34:40.629874Z" } }, "outputs": [], "source": [ "# Accels and scenes\n", "accel_names = ['nanort', 'embree', 'embreeinstanced']\n", "scene_names = lmscene.scenes_small()" ] }, { "cell_type": "code", "execution_count": 7, "id": "79913964", "metadata": { "execution": { "iopub.execute_input": "2021-10-22T11:34:40.634590Z", "iopub.status.busy": "2021-10-22T11:34:40.634120Z", "iopub.status.idle": "2021-10-22T11:34:40.637030Z", "shell.execute_reply": "2021-10-22T11:34:40.637383Z" } }, "outputs": [], "source": [ "def rmse(img1, img2):\n", " return np.sqrt(np.mean((img1 - img2) ** 2))\n", "\n", "def rmse_pixelwised(img1, img2):\n", " return np.sqrt(np.sum((img1 - img2) ** 2, axis=2) / 3)" ] }, { "cell_type": "code", "execution_count": 8, "id": "fe2e5c30", "metadata": { "execution": { "iopub.execute_input": "2021-10-22T11:34:41.813610Z", "iopub.status.busy": "2021-10-22T11:34:41.097908Z", "iopub.status.idle": "2021-10-22T11:35:07.113826Z", "shell.execute_reply": "2021-10-22T11:35:07.113413Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Rendering [scene='fireplace_room']\n", "[I|0.037] Loading asset [name='scene']\n", "[I|0.038] Loading asset [name='camera_main']\n", "[I|0.038] Loading asset [name='model_obj']\n", "[I|0.038] .. Loading OBJ file [path='fireplace_room.obj']\n", "[I|0.038] .. Loading MTL file [path='fireplace_room.mtl']\n", "[I|0.364] .. Loading texture [path='wood.ppm']\n", "[I|0.454] .. Loading texture [path='leaf.ppm']\n", "[I|0.457] .. Loading texture [path='picture8.ppm']\n", "[I|0.489] .. Loading texture [path='wood5.ppm']\n", "[I|0.541] Loading asset [name='accel']\n", "[I|0.545] Building acceleration structure [name='accel']\n", "[I|0.545] .. Flattening scene\n", "[I|0.572] .. Building\n", "[I|1.205] Loading asset [name='film_output']\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "[I|1.283] Loading asset [name='renderer']\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "5856ac95a40f41dfafdb4ec2b78f1500", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/2073600 [00:00" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "[I|9.012] Loading asset [name='accel']\n", "[I|9.012] .. Asset [name='accel'] has been already loaded. Replacing..\n", "[I|9.012] .. {\"intcost\":1.0,\"maxBranchingFactor\":2,\"maxDepth\":18,\"maxLeafSize\":32,\"minLeafSize\":1,\"quality\":1,\"sahBlockSize\":1,\"travcost\":1.0}\n", "[I|9.012] .. {\"compact\":false,\"dynamic\":false,\"filter\":false,\"robust\":false}\n", "[I|9.016] Building acceleration structure [name='accel']\n", "[I|9.016] .. Flattening scene\n", "[I|9.020] .. 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Replacing..\n", "[I|11.449] Loading asset [name='renderer']\n", "[I|11.449] .. Asset [name='renderer'] has been already loaded. Replacing..\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "18bc937cd3ec4dcbafc5016a6346fb76", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/2073600 [00:00" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Rendering [scene='cornell_box_sphere']\n", "[I|13.653] Loading asset [name='scene']\n", "[I|13.653] .. Asset [name='scene'] has been already loaded. Replacing..\n", "[I|13.653] Loading asset [name='camera_main']\n", "[I|13.654] .. Asset [name='camera_main'] has been already loaded. Replacing..\n", "[I|13.654] Loading asset [name='model_obj']\n", "[I|13.654] .. Asset [name='model_obj'] has been already loaded. Replacing..\n", "[I|13.654] .. Loading OBJ file [path='CornellBox-Sphere.obj']\n", "[I|13.654] .. 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Replacing..\n", "[I|23.151] .. {\"intcost\":1.0,\"maxBranchingFactor\":2,\"maxDepth\":18,\"maxLeafSize\":32,\"minLeafSize\":1,\"quality\":1,\"sahBlockSize\":1,\"travcost\":1.0}\n", "[I|23.151] .. {\"compact\":false,\"dynamic\":false,\"filter\":false,\"robust\":false}\n", "[I|23.151] Building acceleration structure [name='accel']\n", "[I|23.151] .. Flattening scene\n", "[I|23.151] .. Building\n", "[I|23.151] Loading asset [name='film_output']\n", "[I|23.151] .. Asset [name='film_output'] has been already loaded. Replacing..\n", "[I|23.231] Loading asset [name='renderer']\n", "[I|23.231] .. Asset [name='renderer'] has been already loaded. Replacing..\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "2f08dc874ffb4385a0335fa49c701148", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/2073600 [00:00" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "[I|24.814] Loading asset [name='accel']\n", "[I|24.814] .. Asset [name='accel'] has been already loaded. Replacing..\n", "[I|24.814] Building acceleration structure [name='accel']\n", "[I|24.814] .. Flattening scene\n", "[I|24.814] .. Building\n", "[I|24.814] Loading asset [name='film_output']\n", "[I|24.815] .. Asset [name='film_output'] has been already loaded. Replacing..\n", "[I|24.896] Loading asset [name='renderer']\n", "[I|24.896] .. Asset [name='renderer'] has been already loaded. Replacing..\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "541f0edbcb8d4a8aa730b2796aabb806", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/2073600 [00:00" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Execute rendering for each scene and accel\n", "rmse_df = pd.DataFrame(columns=accel_names, index=scene_names)\n", "for scene_name in scene_names:\n", " print(\"Rendering [scene='{}']\".format(scene_name))\n", " \n", " # Load scene\n", " scene = lm.load_scene('scene', 'default')\n", " lmscene.load(scene, env.scene_path, scene_name)\n", " \n", " # Use the image for 'accel::sahbvh' as reference\n", " ref = build_and_render(scene, 'sahbvh')\n", " \n", " # Check consistency for other accels\n", " for accel_name in accel_names:\n", " # Render and compute a different image\n", " img = build_and_render(scene, accel_name)\n", " diff = rmse_pixelwised(ref, img)\n", " \n", " # Record rmse\n", " e = rmse(ref, img)\n", " rmse_df[accel_name][scene_name] = e\n", " \n", " # Visualize the difference image\n", " f = plt.figure(figsize=(10,10))\n", " ax = f.add_subplot(111)\n", " im = ax.imshow(diff, origin='lower')\n", " divider = make_axes_locatable(ax)\n", " cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", " plt.colorbar(im, cax=cax)\n", " ax.set_title('{}, sahbvh vs. {}'.format(scene_name, accel_name))\n", " plt.show()" ] }, { "cell_type": "markdown", "id": "45d1eb58", "metadata": {}, "source": [ "### RMSE\n", "\n", "Correct if the values are near zero." ] }, { "cell_type": "code", "execution_count": 9, "id": "ac044037", "metadata": { "execution": { "iopub.execute_input": "2021-10-22T11:35:07.120208Z", "iopub.status.busy": "2021-10-22T11:35:07.117800Z", "iopub.status.idle": "2021-10-22T11:35:07.125629Z", "shell.execute_reply": "2021-10-22T11:35:07.126016Z" } }, "outputs": [ { "data": { "text/html": [ "
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