nerfstudio/docs/notebooks/visualize_samplers.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ray Samplers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "from pyrad.cameras.rays import RayBundle\n",
    "from pyrad.graphs.modules import ray_sampler\n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Spaced Samplers\n",
    "\n",
    "A basic sampler that spaces samples based on a predefined function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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w4Nncf2ro3fzPG7tLkvpoGHv8OwBrgZOSPBlYARxRVbd3D0qyDFgGMDo6OvAiJWm2eukRNsw+YsM4xr8x8FTg41W1O3A78I6Jg6pqeVWNVdXYyMjIoGuUpEVrGMG/GlhdVRc2r79I5xeBJGkABh78VfUr4BdJdmkm7QtcOeg6JKmthnVWz5uAU5ozen4K2OpZkgZkKMFfVZcAD7g5gCSp/7xyV5JaxuCXpJYx+CWpZQx+SWoZg1+SWsbgl6SWMfglqWUMfklqGYNfklrG4JekljH4JallDH5JahmDX5JaxuCXpJYx+CWpZYYW/Ek2SnJxkjOHVYMktdEw9/iPAK4a4volqZWGEvxJtgNeDHxyGOuXpDYb1h7/scDRwH1TDUiyLMl4kvG1a9cOrDBJWuwGHvxJ9gfWVNWK6cZV1fKqGquqsZGRkQFVJ0mL3zD2+PcCDkhyHfBvwHOTfHYIdUhSKw08+KvqnVW1XVUtBQ4CvlFVrx50HZLUVp7HL0kts/EwV15V3wK+NcwaJKlt3OOXpJYx+CWpZQx+SWoZg1+SWsbgl6SWMfglqWUMfklqGYNfklrG4JekljH4JallDH5JahmDX5JaxuCXpJYx+CWpZQx+SWqZYdxzd/sk30xyZZIrkhwx6Bokqc2GcSOWe4Cjqmplki2AFUnOq6orh1CLJLXOMO65e0NVrWye3wpcBWw76Dokqa2Geow/yVJgd+DCSeYtSzKeZHzt2rUDr02SFquhBX+SzYHTgLdU1S0T51fV8qoaq6qxkZGRwRcoSYvUUII/yRI6oX9KVX1pGDVIUlsN46yeACcAV1XVRwa9fklqu2Hs8e8FHAI8N8klzeNFQ6hDklpp4KdzVtV3gQx6vZKkDq/claSWMfglqWUMfklqGYNfklrG4JekljH4JallDH5JahmDX5JaxuCXpJYx+CWpZQx+SWoZg1+SWsbgl6SWMfglqWUMfklqGYNfklpmWPfc3S/JNUmuTfKOYdQgSW01jHvubgR8DHgh8ETg4CRPHHQdktRWw9jj3wO4tqp+WlV3A/8GHDiEOiSplQZ+z11gW+AXXa9XA8+YOCjJMmBZ8/K2JNfMcn1bATfO8r3zjdsyPy2WbVks2wGLaFv+dm7b8pjJJg4j+HtSVcuB5XNdTpLxqhrbACUNndsyPy2WbVks2wFuy0yGcajnl8D2Xa+3a6ZJkgZgGMF/EbBTkh2SPBg4CDh9CHVIUisN/FBPVd2T5I3AOcBGwIlVdUUfVznnw0XziNsyPy2WbVks2wFuy7RSVRt6mZKkecwrdyWpZQx+SWqZRRH8SbZP8s0kVya5IskRk4xJkuOaNhE/SvLUYdQ6kx63Ze8kv0tySfN47zBqnUmShyT5YZJLm215/yRjNkny+eZzuTDJ0iGUOq0et+PQJGu7PpPXD6PWXiXZKMnFSc6cZN68/0y6zbAtC+ZzSXJdksuaOscnmb/BMmzense/nu4BjqqqlUm2AFYkOa+qruwa80Jgp+bxDODjTHLh2DzQy7YAfKeq9h9CfevjLuC5VXVbkiXAd5OcVVU/6BrzOuC3VfW4JAcBHwJeMYxip9HLdgB8vqreOIT6ZuMI4CrgYZPMWwifSbfptgUW1ueyT1VNdbHWBsuwRbHHX1U3VNXK5vmtdP4n2HbCsAOBT1fHD4Atk2wz4FJn1OO2LAjNv/VtzcslzWPi2QQHAp9qnn8R2DdJBlRiT3rcjgUjyXbAi4FPTjFk3n8m6/SwLYvJBsuwRRH83Zo/S3cHLpwwa7JWEfM6UKfZFoBnNocezkqy62Ar613zZ/glwBrgvKqa8nOpqnuA3wGPGmiRPehhOwD+qvkT/ItJtp9k/nxxLHA0cN8U8xfEZ9I4lum3BRbO51LAuUlWNC1rJtpgGbaogj/J5sBpwFuq6pZh1zMXM2zLSuAxVfVk4KPAVwZcXs+q6t6qegqdK7T3SLLbkEualR624wxgaVU9CTiP+/eY55Uk+wNrqmrFsGuZqx63ZUF8Lo0/q6qn0jmk8zdJnt2vFS2a4G+OvZ4GnFJVX5pkyIJpFTHTtlTVLesOPVTV14ElSbYacJnrpapuBr4J7Ddh1h8+lyQbAw8HfjPQ4tbDVNtRVb+pqrual58Enjbg0nq1F3BAkuvodMZ9bpLPThizUD6TGbdlAX0uVNUvm/+uAb5Mp5Nxtw2WYYsi+JvjjycAV1XVR6YYdjrw180343sCv6uqGwZWZI962ZYkW6875ppkDzqf47z7wUwykmTL5vmmwPOBqycMOx14TfP8pcA3ap5dVdjLdkw41noAne9m5p2qemdVbVdVS+m0S/lGVb16wrB5/5lAb9uyUD6XJA9tTuYgyUOBFwCXTxi2wTJssZzVsxdwCHBZcxwW4F3AKEBVfQL4OvAi4FrgDuCwwZfZk1625aXA4UnuAX4PHDQffzCBbYBPpXPznQcBX6iqM5P8HTBeVafT+SX3mSTXAjfR+QGeb3rZjjcnOYDOWVk3AYcOrdpZWICfyZQW6OfyR8CXm/25jYHPVdXZSf43bPgMs2WDJLXMojjUI0nqncEvSS1j8EtSyxj8ktQyBr8ktYzBr9ZIcm/T+fCKpt3FUUke1MwbS3LcNO9dmuSVg6tW6h9P51RrJLmtqjZvnj8a+BxwQVUd08N79wbeugA6okozco9frdRcFr8MeGNzJeTeafq5J3lO7u/ffnFzReUHgWc1045s/gL4TpKVzeNPm/funeRbTUOwq5Oc0nWV9dOTfK/5a+OHSbZomr99OMlFTSOxNwzr30TtsViu3JXWW1X9tLka99ETZr0V+JuquqBplncn8A669viTbAY8v6ruTLITcCow1rx/d2BX4HrgAmCvJD8EPg+8oqouSvIwOlddv47OpfdPT7IJcEGSc6vqZ/3cdrWbwS890AXAR5KcAnypqlbnge3olwDHJ3kKcC+wc9e8H1bVaoCm7cZSOq2Nb6iqi6DTaK+Z/wLgSUle2rz34XRutGHwq28MfrVWksfSCe01wBPWTa+qDyb5Gp2+KBck+fNJ3n4k8GvgyXQOmd7ZNe+uruf3Mv3PWYA3VdU5s9oIaRY8xq9WSjICfAI4fmKDuyQ7VtVlVfUh4CLg8cCtwBZdwx5OZw/+PjpN9TaaYZXXANskeXqzji2alsfn0Gm4t6SZvnPTnVHqG/f41SabNodeltDp1vgZYLLW129Jsg+duzpdAZzVPL83yaXAycC/AKcl+WvgbOD26VZcVXcneQXw0aa18++B59HpEb8UWNl8CbwW+Ms5baU0A0/nlKSW8VCPJLWMwS9JLWPwS1LLGPyS1DIGvyS1jMEvSS1j8EtSy/x/c/mcZtpqWDMAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "num_samples = 1000\n",
    "near = 2\n",
    "far = 5\n",
    "train_stratified = False\n",
    "\n",
    "samplers = {\n",
    "    \"Uniform\": ray_sampler.UniformSampler,\n",
    "    \"Linear in Disparity\": ray_sampler.LinearDisparitySampler,\n",
    "    \"Square Root\": ray_sampler.SqrtSampler,\n",
    "    \"Log Sampler\": ray_sampler.LogSampler,\n",
    "}\n",
    "\n",
    "for name, Sampler in samplers.items():\n",
    "    sampler = Sampler(num_samples=num_samples, train_stratified=train_stratified)\n",
    "\n",
    "    ray_bundle = RayBundle(\n",
    "        origins=torch.ones([1, 3]),\n",
    "        directions=torch.ones([1, 3]),\n",
    "        pixel_area=torch.ones([1, 1]),\n",
    "        nears=torch.ones([1]) * near,\n",
    "        fars=torch.ones([1]) * far,\n",
    "    )\n",
    "\n",
    "    samples = sampler.generate_ray_samples(ray_bundle)\n",
    "    samples.bin_starts.shape\n",
    "\n",
    "    plt.hist(samples.bin_starts, alpha=0.5, bins=100)\n",
    "    plt.xlabel(\"Distance\")\n",
    "    plt.ylabel(\"# Samples\")\n",
    "    plt.title(name)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.8.12 ('pyrad')",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "41f62990c6e03ccb48eec29860b83c64e20fcd45204ae5014afab6809cd6f1f1"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}