{
"cells": [
{
"cell_type": "markdown",
"id": "937022ab-1cd2-4b24-88f1-abd069b38608",
"metadata": {},
"source": [
"# Optimizing patterns\n",
"In this tutorial, we will explain how to use Dr.TVAM to optimize patterns for printing.\n",
"\n",
"
\n",
"\n",
"🚀 **We will cover the following topics:**\n",
" \n",
"
\n",
"
How to setup the optimization
\n",
"
Implementing a basic optimization loop
\n",
"
Extracting and saving the results
\n",
"
\n",
" \n",
"
\n"
]
},
{
"cell_type": "markdown",
"id": "b553dec9-7e83-412f-afb7-546691fe1ba6",
"metadata": {},
"source": [
"We start once again by importing `drtvam` along with other packages:"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "fe0afe5f-207d-4acc-b99b-8a5b9b5b1a95",
"metadata": {},
"outputs": [],
"source": [
"import drtvam\n",
"import mitsuba as mi\n",
"import drjit as dr\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"from tqdm import trange"
]
},
{
"cell_type": "markdown",
"id": "716d89d3-9e91-44b5-a08c-d0651fbb8a46",
"metadata": {},
"source": [
"## 1. Setting up the scene\n",
"\n",
"Setting up Dr.TVAM for optimization is quite similar than what we showed in the previous tutorial, with a few exceptions. We will start again by describing the scene components. For clarity, we will reuse the same printing setup we described in the previous tutorial.\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "86cb62c3-cc0d-4588-8657-0c5b1ba51899",
"metadata": {},
"outputs": [],
"source": [
"scene_dict = {'type': 'scene'}"
]
},
{
"cell_type": "markdown",
"id": "730f121d-2432-47ed-8800-1af3dda20680",
"metadata": {},
"source": [
"### Container geometry\n",
"\n",
"Container geometry is described as before:"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "03d5cd3e-12f9-4fd7-83e5-981cec2316ad",
"metadata": {},
"outputs": [],
"source": [
"vial_params = {\n",
" 'r_int': 5., # 10mm interior diameter\n",
" 'r_ext': 5.5, # 11mm exterior diameter\n",
" 'ior': 1.54, # Index of refraction of the vial\n",
" 'medium': {\n",
" 'ior': 1.5, # Index of refraction of the resin\n",
" 'extinction': 0.1, # Extinction coefficient\n",
" 'albedo': 0. # Purely absorptive\n",
" }\n",
"}\n",
"\n",
"vial = drtvam.geometry.CylindricalVial(vial_params)\n",
"scene_dict |= vial.to_dict()"
]
},
{
"cell_type": "markdown",
"id": "89dd098a-9c63-43e9-a27e-8dc97d6e5985",
"metadata": {},
"source": [
"### Projector\n",
"\n",
"The projector can be initialized like previously, but we can also specify only the number and resolution of the patterns. In that case, all pixels will be initialized at 0.\n",
"\n",
"
\n",
"\n",
"🗒 **Note**\n",
"\n",
"When matching a real printing setup, the projector allows you to specify its full resolution, as well as a *crop* resolution that defines the active area that will be optimized. It is sometimes necessary to do so the optimized resolution so that it fits the memory capabilities of the hardware used for optimization.\n",
"\n",
"
\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "afe1a262-e342-4173-836c-9588f017157c",
"metadata": {},
"outputs": [],
"source": [
"scene_dict['projector'] = {\n",
" 'type': 'collimated',\n",
" 'n_patterns': 1000,\n",
" 'resx': 128,\n",
" 'resy': 128,\n",
" 'pixel_size': 0.1,\n",
" 'motion': 'circular',\n",
" 'distance': 20.\n",
"}"
]
},
{
"cell_type": "markdown",
"id": "5de785c1-0cb1-4105-b642-c969b9a6c010",
"metadata": {},
"source": [
"### Sensor\n",
"\n",
"The sensor is defined as before:"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "7e840100-b61a-4b62-8c84-c78bb6cc42af",
"metadata": {},
"outputs": [],
"source": [
"scene_dict['sensor'] = {\n",
" 'type': 'dda',\n",
" 'to_world': mi.ScalarTransform4f().scale(9),\n",
" 'film': {\n",
" 'type': 'vfilm',\n",
" 'resx': 128,\n",
" 'resy': 128,\n",
" 'resz': 128,\n",
" }\n",
"}"
]
},
{
"cell_type": "markdown",
"id": "042d6709-5ace-4597-8233-7f30496e4677",
"metadata": {},
"source": [
"### Target\n",
"\n",
"In order to optimize patterns, we also need to define the *target surface*, i.e. the shape we want to print. We do that by specifying a 3D mesh file to Mitsuba, either in PLY or OBJ file format. In this example, we will print the well-known [3DBenchy][1] model.\n",
"\n",
"Additionally, we must specify its scale and location in space, so that it fits within the printing medium. We will define a transform such that it is centered around 0, and is $8\\text{mm}$ long.\n",
"\n",
"[1]: https://www.3dbenchy.com/"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "0d537f8c-8f2a-4699-8ce4-1345c63aca64",
"metadata": {},
"outputs": [],
"source": [
"target_mesh = mi.load_dict({\n",
" 'type': 'ply',\n",
" 'filename': 'resources/benchy.ply'\n",
"})\n",
"center = target_mesh.bbox().center()\n",
"scale = 8 / target_mesh.bbox().extents().z\n",
"\n",
"scene_dict['target'] = {\n",
" 'type': 'ply',\n",
" 'filename': 'resources/benchy.ply',\n",
" 'to_world': mi.ScalarTransform4f().scale(scale).translate(-center),\n",
" 'bsdf': {'type': 'null'}\n",
"}"
]
},
{
"cell_type": "markdown",
"id": "a3472eb0-865e-4ad1-a347-1da673bdbb3c",
"metadata": {},
"source": [
"The scene is now ready for loading:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "c130e8ed-ce97-4106-abf4-77472a5a00af",
"metadata": {},
"outputs": [],
"source": [
"scene = mi.load_dict(scene_dict)"
]
},
{
"cell_type": "markdown",
"id": "04f3e17c-fdfb-404f-a494-373517327813",
"metadata": {},
"source": [
"We will also need an integrator, like in the previous tutorial:"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "71614b08-b28d-4013-8293-229a97ce7dc0",
"metadata": {},
"outputs": [],
"source": [
"integrator = mi.load_dict({\n",
" 'type': 'volume',\n",
" 'max_depth': 3,\n",
" 'print_time': 10 # 10s print\n",
"})"
]
},
{
"cell_type": "markdown",
"id": "ad7f2f99-7de0-419c-b082-7b699425ab37",
"metadata": {},
"source": [
"## 2. Optimization setup\n",
"\n",
"In order to run the optimization, we need to define an objective function, a reference, and an optimizer. \n",
"\n",
"Modifiable scene parameters are exposed via Mitsuba's `traverse` mechanism, and the scene is updated by calling `params.update()`"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "72242398-5126-415d-982d-1a1e69f54596",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"SceneParameters[\n",
" --------------------------------------------------------------------------------------------------------\n",
" Name Flags Type Parent\n",
" --------------------------------------------------------------------------------------------------------\n",
" projector.active_data ∂ Float Emitter\n",
" projector.active_pixels UInt Emitter\n",
" sensor.to_world ScalarTransform4d Sensor\n",
" sensor.film.data ∂ TensorXf Film\n",
" target.silhouette_sampling_weight float PLYMesh\n",
" target.faces UInt PLYMesh\n",
" target.vertex_positions ∂, D Float PLYMesh\n",
" target.vertex_normals ∂, D Float PLYMesh\n",
" target.vertex_texcoords ∂ Float PLYMesh\n",
" vial_exterior.bsdf.eta float SmoothDielectric\n",
" vial_exterior.silhouette_sampling_weight float Cylinder\n",
" vial_exterior.to_world ∂, D Transform4f Cylinder\n",
" vial_interior.bsdf.eta float SmoothDielectric\n",
" vial_interior.interior_medium.scale float HomogeneousMedium\n",
" vial_interior.interior_medium.albedo.value.value ∂ Float UniformSpectrum\n",
" vial_interior.interior_medium.sigma_t.value.value ∂ Float UniformSpectrum\n",
" vial_interior.silhouette_sampling_weight float Cylinder\n",
" vial_interior.to_world ∂, D Transform4f Cylinder\n",
"]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"params = mi.traverse(scene)\n",
"params"
]
},
{
"cell_type": "markdown",
"id": "dd5cfe84-f289-43fd-8e95-b7a0d8fad336",
"metadata": {},
"source": [
"### Reference\n",
"In its simplest form, the reference is generated by converting the target mesh into a binary occupancy grid. We provide a convenience function to do that:"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "69e09535-ec7f-4c44-8d5a-db0b9df76d76",
"metadata": {},
"outputs": [],
"source": [
"from drtvam.utils import discretize\n",
"target = discretize(scene)"
]
},
{
"cell_type": "markdown",
"id": "e4518179-cc2f-4d62-9836-cdc794bf970d",
"metadata": {},
"source": [
"Let's visualize one slice of the target:"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "278e67e5-0ba6-4201-96ce-401437746d24",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(-0.5, 127.5, 127.5, -0.5)"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(target[64], cmap='turbo', interpolation='none')\n",
"plt.axis('off')"
]
},
{
"cell_type": "markdown",
"id": "108a5b76-1d43-464e-a6a9-ba4fa52f8524",
"metadata": {},
"source": [
"We do not need the target surface anymore, so we move it far away from the vial so it doesn't affect performance when rendering:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "c45bee18-c63c-4baa-94f6-0978abb88d73",
"metadata": {},
"outputs": [],
"source": [
"params['target.vertex_positions'] += 1e5\n",
"params.update();"
]
},
{
"cell_type": "markdown",
"id": "6d0994bf-82e6-4308-b2a5-7d9784398e8c",
"metadata": {},
"source": [
"### Objective function\n",
"\n",
"Objective functions are implemented as `Loss` sub-classes. We will use the thresholded loss function introduced by Wechsler et al [[2024]][1]. Parameters are provided as a dictionary, specifying the lower (`tl`) and upper (`tu`) thresholds.\n",
"\n",
"[1]: https://opg.optica.org/oe/fulltext.cfm?uri=oe-32-8-14705&id=548744"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "bc41d574-1466-46c8-88cb-b998a58f7563",
"metadata": {},
"outputs": [],
"source": [
"from drtvam.loss import ThresholdedLoss\n",
"loss_fn = ThresholdedLoss({'tl': 0.9, 'tu': 0.95})"
]
},
{
"cell_type": "markdown",
"id": "80456bea-d54a-4127-a634-0092674900e6",
"metadata": {},
"source": [
"### Optimizer\n",
"We now need to define the parameters to optimize, and provide them to an *optimizer*, which will update them at each optimization step."
]
},
{
"cell_type": "markdown",
"id": "3fd72ea1-a904-489a-897d-39e089ab5c15",
"metadata": {},
"source": [
"All elements in the list above can be modified, and the changes are propagated to the scene via `params.update()`. The parameter we are interested in optimizing is `projector.active_data`, which contains the values of all the active projector pixels, currently initialized at 0.\n",
"\n",
"We will use the `LinearLBGFS` optimizer, which implements the L-BFGS update rule, with a performance optimization based on the consideration that the pattern projection is linear with respects to the patterns. To use it, we need to provide two functions: one to evaluate the objective function, and one to evaluate the gradient."
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "6d5de7cf-aa9a-4c4c-86cc-6161374fbb07",
"metadata": {},
"outputs": [],
"source": [
"def eval_vol(vars):\n",
" params[patterns_key] = vars[patterns_key]\n",
" params.update()\n",
" vol = mi.render(scene, params, integrator=integrator, spp=spp, spp_grad=spp_grad, seed=it)\n",
" return vol\n",
"\n",
"def eval_loss(y):\n",
" return loss_fn(y, target)"
]
},
{
"cell_type": "markdown",
"id": "242db376-64c2-4bbf-be53-68d319df2d9d",
"metadata": {},
"source": [
"We can now initialize the optimizer with these functions:"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "2119eaea-a121-4698-8bcb-d5bc9f1db17d",
"metadata": {},
"outputs": [],
"source": [
"from drtvam.lbfgs import LinearLBFGS\n",
"opt = LinearLBFGS(render_fn=eval_vol, loss_fn=eval_loss)"
]
},
{
"cell_type": "markdown",
"id": "2c486c59-3a48-47b6-8bc5-909703c81b0c",
"metadata": {},
"source": [
"Finally, we need to provide it with the parameters to optimize:"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "6e640512-5e14-4257-b4f6-505d7a75915c",
"metadata": {},
"outputs": [],
"source": [
"patterns_key = 'projector.active_data'\n",
"opt[patterns_key] = params[patterns_key]"
]
},
{
"cell_type": "markdown",
"id": "9892cb29-d530-4522-a5b1-eadd3d2d159c",
"metadata": {},
"source": [
"## 3. Running the optimization\n",
"\n",
"We are now ready to run the optimization. At each iteration, we will project the patterns, compute the loss and call `dr.backward` to backpropagate it to obtain the parameter gradients. The parameters are then updated by the optimizer, and we finally clip potential negative values to 0. We will do that for 40 iterations.\n",
"\n",
"Projecting the patterns is done again with `mi.render`, with the same arguments. Note that we can provide both `spp` and `spp_grad`, which define the sample count for the evaluatin of the forward model and the backpropagation, respectively."
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "4e00cf7d-ef48-4092-99d4-a6ff503a56e9",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 40/40 [00:16<00:00, 2.41it/s]\n"
]
}
],
"source": [
"spp = 8\n",
"spp_grad = 16\n",
"\n",
"for it in trange(40):\n",
" # Update scene\n",
" params.update(opt)\n",
" # Simulate projections\n",
" vol = mi.render(scene, params, integrator=integrator, spp=spp, spp_grad=spp_grad, seed=it)\n",
" # Evaluate objective function\n",
" loss = loss_fn(vol, target)\n",
" # Backpropagate\n",
" dr.backward(loss)\n",
" # Update patterns\n",
" opt.step(vol, loss)\n",
" # Clip negative values\n",
" opt[patterns_key] = dr.maximum(dr.detach(opt[patterns_key]), 0.)"
]
},
{
"cell_type": "markdown",
"id": "c4d3138f-8622-4c17-ac30-23dcfd7df1af",
"metadata": {},
"source": [
"## 4. Visualizing the results\n",
"\n",
"We can now evaluate the optimized results. We can start by rendering the final state of the optimization:"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "24cb211a-c208-4b19-8cb0-c438156dc93c",
"metadata": {},
"outputs": [],
"source": [
"params.update(opt)\n",
"vol_final = mi.render(scene, params, integrator=integrator, spp=64, seed=0)"
]
},
{
"cell_type": "markdown",
"id": "d728695a-b792-47eb-aa87-916b37036d54",
"metadata": {},
"source": [
"We can now look at the result slice by slice, and compare it with the target:"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "dec31e5b-48d6-44de-8069-a8e7b2cfc69a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(-0.5, 127.5, 127.5, -0.5)"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"layer = 64\n",
"fig = plt.figure(1, figsize=(16, 5))\n",
"gs = fig.add_gridspec(1, 3, wspace=0.2)\n",
"\n",
"ax = fig.add_subplot(gs[0])\n",
"im = ax.imshow(vol_final[layer], interpolation='none', cmap='turbo')\n",
"ax.set_title(\"Recorded absorption\")\n",
"cbax = ax.inset_axes([1.02, 0, 0.04, 1], transform=ax.transAxes)\n",
"fig.colorbar(im, cax=cbax)\n",
"ax.axis('off')\n",
"\n",
"ax = fig.add_subplot(gs[1])\n",
"ax.imshow(vol_final[layer] > 0.9, interpolation='none', cmap='turbo')\n",
"ax.set_title(\"Thresholded print\")\n",
"ax.axis('off')\n",
"\n",
"ax = fig.add_subplot(gs[2])\n",
"ax.imshow(target[layer], interpolation='none', cmap='turbo')\n",
"ax.set_title(\"Target\")\n",
"ax.axis('off')"
]
},
{
"cell_type": "markdown",
"id": "deddfe89-8f9f-43cc-8a87-0428a5023b8b",
"metadata": {},
"source": [
"Another useful metric is to look at the *histogram* of recorded absorption. Ideally, we can observe good separation between object and non-object voxels, which indicates that polymerizing only the object part of the volume is feasible."
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "3f41294f-c96d-41f0-8557-7b8c5430f617",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig = plt.figure(figsize=(10, 5))\n",
"obj_mask = target.numpy().flatten() > 0.\n",
"\n",
"voxels_final = vol_final.numpy().flatten()\n",
"bins = np.linspace(0, 1, 500)\n",
"plt.hist(voxels_final[obj_mask], bins=500, label=\"Object voxels\", alpha=0.55)\n",
"plt.hist(voxels_final[~obj_mask], bins=500, label=\"Non-object voxels\", alpha=0.55)\n",
"plt.vlines(0.9, 0, 1e6, linestyle='--', color='red', label='Lower threshold')\n",
"plt.vlines(0.95, 0, 1e6, linestyle='--', color='green', label='Upper threshold')\n",
"\n",
"plt.yscale('log')\n",
"plt.ylabel(\"# Voxels\")\n",
"plt.xlabel(\"Received dose\")\n",
"plt.legend()"
]
},
{
"cell_type": "markdown",
"id": "0031a79e-4183-4277-9dca-cf3f2a0e03fa",
"metadata": {},
"source": [
"Finally, we can extract the projector patterns and visualize them:"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "e5f2e4ac-0ecb-45b1-a86a-39514c6d144a",
"metadata": {},
"outputs": [],
"source": [
"patterns = scene.emitters()[0].patterns()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "1732dc27-3259-4ecd-8df6-16631ce21754",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig = plt.figure(1, figsize=(26, 5))\n",
"gs = fig.add_gridspec(1, 5, wspace=0.2)\n",
"pattern_count = patterns.shape[0]\n",
"\n",
"for i in range(5):\n",
" pattern_id = i * pattern_count // 5\n",
" ax = fig.add_subplot(gs[i])\n",
" im = ax.imshow(patterns[pattern_id], vmax=7e-3, interpolation='none', cmap='turbo')\n",
" ax.set_title(f\"{pattern_id}/{pattern_count}\")\n",
" ax.axis('off')\n",
"\n",
"cbax = ax.inset_axes([1.02, 0, 0.04, 1], transform=ax.transAxes)\n",
"fig.colorbar(im, cax=cbax)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.9.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}