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Merge pull request #44 from rnd-team-dev/r0.15.1
R0.15.1
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‎CHANGELOG.rst‎

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Release history
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===============
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`v0.15.1` - 2023-03-16
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----------------------
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Added
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~~~~~
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- OpenCV-like intrinsic matrix in camera setup
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- configurable denoiser start frame
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Changed
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~~~~~~~
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- ovrlaping refractive volumes handling
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`v0.15.0` - 2022-12-30
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----------------------
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- this changelog, markdown description content type tag for PyPI
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- use [Semantic Versioning](https://semver.org/spec/v2.0.0.html)
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.. _`v0.15.1`: https://github.com/rnd-team-dev/plotoptix/releases/tag/v0.15.1
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.. _`v0.15.0`: https://github.com/rnd-team-dev/plotoptix/releases/tag/v0.15.0
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.. _`v0.14.4`: https://github.com/rnd-team-dev/plotoptix/releases/tag/v0.14.4
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.. _`v0.14.3`: https://github.com/rnd-team-dev/plotoptix/releases/tag/v0.14.3

‎examples/1_basics/12_camera_shaders.ipynb‎

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"display_name": "Python 3 (ipykernel)",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.4"
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"version": "3.10.6"
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‎examples/1_basics/13_camera_calibration.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Camera calibration\n",
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"\n",
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"Pinhole and thin-lens cameras accept OpenCV-like intrinsics matrix in setup/update functions. This notebook illustrates how intrinsic parameters should be provided and how you can recover them with OpenCV camera calibration."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import cv2 as cv\n",
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"from plotoptix import TkOptiX"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Setup the raytracer:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"rt = TkOptiX(start_now=False)\n",
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"\n",
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"rt.set_param(min_accumulation_step=4,\n",
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" max_accumulation_frames=512)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Add chess board pattern used for calibration."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"rx = 10\n",
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"ry = 10\n",
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"n = 11\n",
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"\n",
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"x = np.linspace(0, rx, n)\n",
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"y = np.linspace(0, ry, n)\n",
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"X, Y = np.meshgrid(x, y)\n",
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"\n",
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"# positions of cubes\n",
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"xyz = np.stack((X.flatten(), Y.flatten(), np.zeros(n**2))).T - np.array([0, 0, 0.15])\n",
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"\n",
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"widx = [i for i in range(0,xyz.shape[0]) if i % 2 == 0]\n",
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"bidx = [i for i in range(0,xyz.shape[0]) if i % 2 == 1]\n",
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"\n",
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"xp = np.linspace(1, rx, n-1)\n",
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"yp = np.linspace(1, ry, n-1)\n",
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"Xp, Yp = np.meshgrid(xp, yp)\n",
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"xyzp = np.stack((Xp.flatten(), Yp.flatten(), np.zeros((n-1)**2))).T.astype(np.float32)\n",
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"#rt.set_data(\"points\", xyzp, r=0.1, c=0.9) # points to confirm true positions of objpoints\n",
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"\n",
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"rt.set_data(\"wcubes\", xyz[widx,:], u=[0.998, 0, 0], v=[0, 0.998, 0], w=[0, 0, 0.15], c=0.93, geom=\"Parallelepipeds\")\n",
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"rt.set_data(\"bcubes\", xyz[bidx,:], u=[0.998, 0, 0], v=[0, 0.998, 0], w=[0, 0, 0.15], c=0.15, geom=\"Parallelepipeds\")\n",
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"rt.set_data(\"base\", [-0.5, -0.5, -0.3], u=[12, 0, 0], v=[0, 12, 0], w=[0, 0, 0.2], c=0.9, geom=\"Parallelepipeds\")\n",
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"\n",
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"rt.set_data(\"plane\", [-20, -20, -1], u=[50, 0, 0], v=[0, 50, 0], c=0.9, geom=\"Parallelograms\") # a wall behind cubes\n",
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"\n",
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"rt.setup_area_light(\"light1\", center=[15, 4, 15], target=[5, 4, 0], u=7, v=7, color=[8.5, 8, 7.5])\n",
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"\n",
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"rt.set_ambient([0.1, 0.2, 0.4])\n",
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"rt.set_background(0)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Camera setup. Absolute scale in [mm] is used, though it requires to specify sensor height (Y dimension)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"sensor_height = 24 # [mm]\n",
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"fx = 17 # [mm]\n",
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"fy = 17 # [mm]\n",
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"cx = 3 # [mm]\n",
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"cy = 0 # [mm]\n",
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"\n",
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"# OpenCV-like camera intrinsic matrix\n",
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"cam_mat = np.array([[fx, 0, cx], [0, fy, cy], [0, 0, 1]], dtype=np.float32)\n",
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"\n",
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"eye = [7, 7, 10]\n",
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"tgt = [6, 6, 0]\n",
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"up = [0, -1, 0]\n",
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"\n",
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"rt.setup_camera(\n",
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" \"cam1\", cam_type=\"ThinLens\",\n",
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" eye=eye, target=tgt, up=up,\n",
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" camera_matrix=cam_mat,\n",
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" sensor_height=sensor_height,\n",
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" glock=True\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Start the ray tracing:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {
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"scrolled": true
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},
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"outputs": [],
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"source": [
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"rt.start()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Collect calibration images.**\n",
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"\n",
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"Calibration with OpenCV is performed for a fixed image size, this it is set below to 1300x950 to avoid changes caused by the GUI.\n",
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"\n",
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"Change the anlgle of view and/or camera target and wait until callback notifies image was captured. Collect a few images. These will be used to reconstruct camera parameters."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"1 images captured\n",
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"2 images captured\n",
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"3 images captured\n",
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"4 images captured\n",
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"5 images captured\n",
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"6 images captured\n",
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"7 images captured\n"
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]
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}
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],
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"source": [
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"width = 1500\n",
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"height = 950\n",
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"\n",
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"rt.set_rt_size((width, height))\n",
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"\n",
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"imgpoints = []\n",
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"objpoints = []\n",
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"\n",
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"def image_ready(rt: TkOptiX) -> None:\n",
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" gray = cv.cvtColor(rt._img_rgba, cv.COLOR_BGR2GRAY)\n",
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" retval, corners = cv.findChessboardCorners(gray, (n-1, n-1))\n",
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" if retval:\n",
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" corners2 = cv.cornerSubPix(\n",
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" gray, corners, (5,5), (-1,-1),\n",
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" (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 10, 0.001)\n",
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" )\n",
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" imgpoints.append(corners2)\n",
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" objpoints.append(100*xyzp.astype(np.float32))\n",
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"\n",
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" print(len(imgpoints), \"images captured\")\n",
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" else:\n",
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" print(\"skip image\")\n",
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" \n",
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"rt.set_accum_done_cb(image_ready)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Run camera calibration. OpenCV returns calues in [pixels] so they need to appropriate scaling to get values back in [mm]."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"fx: 672.6737619162795\n",
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"fy: 672.6596888212799\n",
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"fx: 16.99386345893759 [mm]\n",
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"fy: 16.993507928116546 [mm]\n",
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"cx: 0.12460680641213917\n",
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"cy: -0.000521407446712252\n",
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"cx: 2.99056335389134 [mm]\n",
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"cy: -0.012513778721094049 [mm]\n",
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"dist: [[-2.07361708e-04 4.49837393e-04 9.99845034e-06 -4.78913174e-06\n",
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" -2.68033315e-04]]\n"
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]
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}
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],
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"source": [
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"img_size = rt.get_size()\n",
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"pixel_pitch = sensor_height / img_size[1]\n",
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"\n",
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"ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(objpoints, imgpoints, img_size, None, None)\n",
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"\n",
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"print(\"fx:\", mtx[0,0])\n",
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"print(\"fy:\", mtx[1,1])\n",
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"print(\"fx:\", pixel_pitch * mtx[0,0], \"[mm]\")\n",
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"print(\"fy:\", pixel_pitch * mtx[1,1], \"[mm]\")\n",
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"print(\"cx:\", mtx[0,2] / img_size[0] - 0.5)\n",
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"print(\"cy:\", mtx[1,2] / img_size[1] - 0.5)\n",
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"print(\"cx:\", sensor_height * (mtx[0,2] / img_size[0] - 0.5), \"[mm]\")\n",
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"print(\"cy:\", sensor_height * (mtx[1,2] / img_size[1] - 0.5), \"[mm]\")\n",
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"print(\"dist:\", dist)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Try another set of parameters and re-run image capturing and calibration."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [],
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"source": [
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"sensor_height = 24 # [mm]\n",
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"fx = 21 # [mm]\n",
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"fy = 18 # [mm]\n",
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"cx = 0 # [mm]\n",
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"cy = -2 # [mm]\n",
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"\n",
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"# OpenCV-like camera intrinsic matrix\n",
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"cam_mat = np.array([[fx, 0, cx], [0, fy, cy], [0, 0, 1]], dtype=np.float32)\n",
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"\n",
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"rt.update_camera(\"cam1\",\n",
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" camera_matrix=cam_mat,\n",
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" sensor_height=sensor_height,\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Close the ray-tracer."
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]
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},
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"cell_type": "code",
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"execution_count": 33,
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"metadata": {},
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"outputs": [],
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"source": [
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"rt.close()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎examples/1_basics/4_materials_and_glass_colors.ipynb‎

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‎examples/1_basics/4_materials_configuration.ipynb‎

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