{ "cells": [ { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "# Mesh I/O and manipulation" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "nbsphinx": "hidden", "tags": [] }, "outputs": [], "source": [ "import drjit as dr\n", "import mitsuba as mi\n", "\n", "mi.set_variant(\"cuda_ad_rgb\", \"llvm_ad_rgb\")" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "## Reading a mesh from disk\n", "\n", "Mitsuba provides an abstract `Shape` class to handle all geometric shapes. For triangle meshes, it has a concrete class `Mesh` that is further extended by 3 plugins which can load meshes directly from a file:\n", "\n", "- [OBJ][1]: handles meshes containing triangles and quadrilaterals from Wavefront OBJ files\n", "- [PLY][2]: handles Stanford PLY format meshes (both the ASCII and binary format)\n", "- [Serialized][3]: Mitsuba 0.6 serialized mesh format.\n", "\n", "As any other Mitsuba object, we can use the `load_dict` function to instantiate one of these three plugins. They each have their own specific input parameters which you'll find in their respective documentation, but here are the input parameters they all share:\n", "\n", "- **filename**: filename of the mesh file that should be loaded\n", "- **face_normals**: when set to true, any existing or computed vertex normals are discarded and face normals will instead be used during rendering. This gives the rendered object a faceted appearance.\n", "- **to_world**: specifies an linear object-to-world transformation. \n", "\n", "Let's now load a mesh and start playing with it.\n", "\n", "[1]: https://mitsuba.readthedocs.io/en/latest/src/generated/plugins_shapes.html#wavefront-obj-mesh-loader-obj\n", "[2]: https://mitsuba.readthedocs.io/en/latest/src/generated/plugins_shapes.html#ply-stanford-triangle-format-mesh-loader-ply\n", "[3]: https://mitsuba.readthedocs.io/en/latest/src/generated/plugins_shapes.html#serialized-mesh-loader-serialized" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "PLYMesh[\n", " name = \"bunny.ply\",\n", " bbox = BoundingBox3f[\n", " min = [-0.0779344, -0.0611472, -0.0738726],\n", " max = [0.0874787, 0.0992267, 0.0468007]\n", " ],\n", " vertex_count = 35947,\n", " vertices = [843 KiB of vertex data],\n", " face_count = 69451,\n", " faces = [814 KiB of face data],\n", " face_normals = 0\n", "]\n" ] } ], "source": [ "bunny = mi.load_dict({\n", " \"type\": \"ply\",\n", " \"filename\": \"../scenes/meshes/bunny.ply\",\n", " \"face_normals\": False,\n", " \"to_world\": mi.ScalarTransform4f().rotate([0, 0, 1], angle=10),\n", "})\n", "\n", "print(bunny)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The string representation of a `Mesh` object gives an overview of its size. If you wish to access some of these values, they are available through the following methods `Shape.bbox()`, `Mesh.vertex_count()`, `Mesh.face_count()`." ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "## Procedural mesh \n", "\n", "By directly using the `Mesh` class, it is also possible to procedurally create a mesh. To illustrate this, we will build a spanning triangle disk and give it a wavy fringe. The exact details of how the vertex positions and face indices are generated are not important for the purposes of this guide. However, we do leave them as comments in the code." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# Wavy disk construction\n", "#\n", "# Let N define the total number of vertices, the first N-1 vertices will compose\n", "# the fringe of the disk, while the last vertex should be placed at the center.\n", "# The first N-1 vertices must have their height modified such that they oscillate\n", "# with some given frequency and amplitude. To compute the face indices, we define\n", "# the first vertex of every face to be the vertex at the center (idx=N-1) and the\n", "# other two can be assigned sequentially (modulo N-2).\n", "\n", "# Disk with a wavy fringe parameters\n", "N = 100\n", "frequency = 12.0\n", "amplitude = 0.4\n", "\n", "# Generate the vertex positions\n", "theta = dr.linspace(mi.Float, 0.0, dr.two_pi, N)\n", "x, y = dr.sincos(theta)\n", "z = amplitude * dr.sin(theta * frequency)\n", "vertex_pos = mi.Point3f(x, y, z)\n", "\n", "# Move the last vertex to the center\n", "vertex_pos[dr.arange(mi.UInt32, N) == N - 1] = 0.0\n", "\n", "# Generate the face indices\n", "idx = dr.arange(mi.UInt32, N - 1)\n", "face_indices = mi.Vector3u(N - 1, (idx + 1) % (N - 2), idx % (N - 2))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The `Mesh` constructor allocates all the necessary buffers to hold its data. Specifically, the constructor takes as arguments the number of vertices and faces which will then be fixed. It is not possible to edit a mesh in a way that would require the buffers to be resized (more/less faces for examples), a new `Mesh` would need to be created for such use cases.\n", "The constructor can also takes two boolean arguments `has_vertex_normals` and `has_vertex_texcoords` that must also be know at the construction of the object, in order to allocate the appropriate buffers." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# Create an empty mesh (allocates buffers of the correct size)\n", "mesh = mi.Mesh(\n", " \"wavydisk\",\n", " vertex_count=N,\n", " face_count=N - 1,\n", " has_vertex_normals=False,\n", " has_vertex_texcoords=False,\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In order to assign our existing vertex positions and face indices to the newly created `Mesh` object we will use the `traverse()` mechanism. All of the allocated buffers of a `Mesh` object are exposed, and can therefore be modified with this mechanism. This approach has the advantage of simplifying some of the assignment operations. In addition, if any vertex position is modified, a call to `SceneParameters.update()` will trigger recomputation of both the bounding box and vertex normals.\n", "\n", "One caveat here is that meshes in Mitsuba store their data in **flat linear buffers**. Hence it is necessary to change the layout of the array of vertex positions and face indices computed above. Luckily, Dr.Jit provides `dr.ravel()` which does exactly that. The complement of this function is `dr.unravel()` which will convert a flat linear array to a structure-of-array of the specific type (e.g., `Point3f`)." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[(Mesh[\n", " name = \"wavydisk\",\n", " bbox = BoundingBox3f[\n", " min = [-0.999874, -0.999497, -0.399547],\n", " max = [0.999874, 1, 0.399547]\n", " ],\n", " vertex_count = 100,\n", " vertices = [1.17 KiB of vertex data],\n", " face_count = 99,\n", " faces = [1.16 KiB of face data],\n", " face_normals = 0\n", "], {'vertex_positions', 'faces'})]\n" ] } ], "source": [ "mesh_params = mi.traverse(mesh)\n", "mesh_params[\"vertex_positions\"] = dr.ravel(vertex_pos)\n", "mesh_params[\"faces\"] = dr.ravel(face_indices)\n", "print(mesh_params.update())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And now let's take a look at our new mesh!" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "scene = mi.load_dict({\n", " \"type\": \"scene\",\n", " \"integrator\": {\"type\": \"path\"},\n", " \"light\": {\"type\": \"constant\"},\n", " \"sensor\": {\n", " \"type\": \"perspective\",\n", " \"to_world\": mi.ScalarTransform4f().look_at(\n", " origin=[0, -5, 5], target=[0, 0, 0], up=[0, 0, 1]\n", " ),\n", " },\n", " \"wavydisk\": mesh,\n", "})\n", "\n", "img = mi.render(scene)\n", "\n", "from matplotlib import pyplot as plt\n", "\n", "plt.axis(\"off\")\n", "plt.imshow(mi.util.convert_to_bitmap(img));" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "## Writing a mesh to disk\n", "\n", "No matter how a `Mesh` object was loaded or built, it can always be exported to a [PLY file format](https://en.wikipedia.org/wiki/PLY_(file_format)) using the `Mesh.write_ply()` method. No other file formats are currently supported.\n", "\n", "
\n", "\n", "🗒 **Note**\n", "\n", "Any mesh attribute (see below) that is attached to the object at the time when `Mesh.write_ply()` is called will be written to output file as a property. Mitsuba therefore allows you to create complex procedural properties for your meshes and export them to be used in some other context entirely.\n", "
" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "mesh.write_ply(\"wavydisk.ply\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Adding and editing attributes\n", "\n", "Meshes in Mitsuba can have additional attributes per face or per vertex. Each attribute is either one or several floating point numbers, no other types are supported.\n", "\n", "The `Mesh.add_attribute()` methods lets you define new attributes by giving them a name, a number of feilds, and their initial values. The attribute name must be prefixed with either `vertex_` or `face_`, as this defines whether the attribute is defined for each face or for each vertex. For this example, we will be adding a RGB color to each vertex. \n", "\n", "Moreover, Mitsuba 3 has a [mesh attribute][1] texture plugin that conviently allows you to visualize attributes.\n", "\n", "[1]: https://mitsuba.readthedocs.io/en/latest/src/generated/plugins_textures.html#mesh-attribute-texture-mesh-attribute" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "mesh = mi.load_dict({\n", " \"type\": \"ply\",\n", " \"filename\": \"wavydisk.ply\",\n", " \"bsdf\": {\n", " \"type\": \"diffuse\",\n", " \"reflectance\": {\n", " \"type\": \"mesh_attribute\",\n", " \"name\": \"vertex_color\", # This will be used to visualize our attribute\n", " },\n", " },\n", "})\n", "\n", "# Needs to start with vertex_ or face_\n", "attribute_size = mesh.vertex_count() * 3\n", "mesh.add_attribute(\n", " \"vertex_color\", 3, [0] * attribute_size\n", ") # Add 3 floats per vertex (initialized at 0)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Once an attribute is created it can still be modified using the `traverse()` mechanism. As shown below, the attribute's buffer will be exposed with a key corresponding to the attribute's name." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "SceneParameters[\n", " ---------------------------------------------------------------------------------\n", " Name Flags Type Parent\n", " ---------------------------------------------------------------------------------\n", " bsdf.reflectance.scale float MeshAttribute\n", " silhouette_sampling_weight float PLYMesh\n", " faces UInt PLYMesh\n", " vertex_positions ∂, D Float PLYMesh\n", " vertex_normals ∂, D Float PLYMesh\n", " vertex_texcoords ∂ Float PLYMesh\n", " vertex_color ∂ Float PLYMesh\n", "]" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mesh_params = mi.traverse(mesh)\n", "mesh_params" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can now easily change the values of the attribute using some simple Dr.Jit arithmetic." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[(PLYMesh[\n", " name = \"wavydisk.ply\",\n", " bbox = BoundingBox3f[\n", " min = [-0.999874, -0.999497, -0.399547],\n", " max = [0.999874, 1, 0.399547]\n", " ],\n", " vertex_count = 100,\n", " vertices = [3.52 KiB of vertex data],\n", " face_count = 99,\n", " faces = [1.16 KiB of face data],\n", " face_normals = 0,\n", " mesh attributes = [\n", " vertex_color: 3 floats\n", " ]\n", " ],\n", " {'vertex_color'})]" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "N = mesh.vertex_count()\n", "\n", "vertex_colors = dr.zeros(mi.Float, 3 * N)\n", "fringe_vertex_indices = dr.arange(mi.UInt, N - 1)\n", "dr.scatter(vertex_colors, 1, fringe_vertex_indices * 3) # Fringe is red\n", "dr.scatter(vertex_colors, 1, [(N - 1) * 3 + 2]) # Center is blue\n", "\n", "mesh_params[\"vertex_color\"] = vertex_colors\n", "mesh_params.update()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And visualize the result!" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "scene = mi.load_dict(\n", " {\n", " \"type\": \"scene\",\n", " \"integrator\": {\"type\": \"path\"},\n", " \"light\": {\"type\": \"constant\"},\n", " \"sensor\": {\n", " \"type\": \"perspective\",\n", " \"to_world\": mi.ScalarTransform4f().look_at(\n", " origin=[0, -5, 5], target=[0, 0, 0], up=[0, 0, 1]\n", " ),\n", " },\n", " \"wavydisk\": mesh,\n", " }\n", ")\n", "\n", "img = mi.render(scene)\n", "\n", "plt.axis(\"off\")\n", "plt.imshow(mi.util.convert_to_bitmap(img));" ] } ], "metadata": { "file_extension": ".py", "interpreter": { "hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6" }, "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": "3.10.12" }, "metadata": { "interpreter": { "hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6" } }, "mimetype": "text/x-python", "name": "python", "npconvert_exporter": "python", "pygments_lexer": "ipython3", "version": 3 }, "nbformat": 4, "nbformat_minor": 4 }