Add plotly visualization examples

Summary: Add examples of using the Plotly visualization functions to the corresponding tutorial notebooks.

Reviewed By: nikhilaravi

Differential Revision: D23879109

fbshipit-source-id: ea8c45aa6c828eb2f6ea2ae1c8846adc486f92e0

docs/tutorials/render_colored_points.ipynb

@@ -67,6 +67,7 @@
     "\n",
     "# Data structures and functions for rendering\n",
     "from pytorch3d.structures import Pointclouds\n",
+    "from pytorch3d.visualization import AxisArgs, plot_pointclouds\n",
     "from pytorch3d.renderer import (\n",
     "    look_at_view_transform,\n",
     "    FoVOrthographicCameras, \n",
@@ -286,6 +287,86 @@
     "plt.grid(\"off\")\n",
     "plt.axis(\"off\");"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### View pointclouds in Plotly figures\n",
+    "\n",
+    "Here we use the PyTorch3D function `plot_pointclouds` to render the Pointcloud in a Plotly figure. `plot_pointclouds` returns a plotly figure with a trace for each pointcloud."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plot_pointclouds(point_cloud)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We will now render a batch of pointclouds. The first pointcloud is the same as above, and the second is all-black and offset by 2 in all dimensions so we can see them on the same plot. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "point_cloud_batch = Pointclouds(points=[verts, verts + 2], features=[rgb, torch.zeros_like(rgb)])\n",
+    "# render both in the same plot\n",
+    "fig = plot_pointclouds(point_cloud_batch)\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# render both in 1 row in different subplots\n",
+    "fig2 = plot_pointclouds(point_cloud_batch, in_subplots=True, ncols=2)\n",
+    "fig2.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# modify the plotly figure height and width\n",
+    "fig2.update_layout(height=500, width=500)\n",
+    "fig2.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also modify the axis arguments and axis backgrounds, and title our plots."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig3 = plot_pointclouds(point_cloud_batch, xaxis={\"backgroundcolor\":\"rgb(200, 200, 230)\"},\n",
+    "                        yaxis={\"backgroundcolor\":\"rgb(230, 200, 200)\"},\n",
+    "                        zaxis={\"backgroundcolor\":\"rgb(200, 230, 200)\"}, \n",
+    "                        subplot_titles=[\"2 pointclouds\"], # this should have a title for each subplot, titles can be \"\"\n",
+    "                        axis_args=AxisArgs(showgrid=True))\n",
+    "fig3.show()"
+   ]
   }
  ],
  "metadata": {
@@ -298,9 +379,9 @@
    "bento/extensions/theme/main.css": true
   },
   "kernelspec": {
-   "display_name": "pytorch3d (local)",
+   "display_name": "pytorch3d_etc (local)",
    "language": "python",
-   "name": "pytorch3d_local"
+   "name": "pytorch3d_etc_local"
   },
   "language_info": {
    "codemirror_mode": {

docs/tutorials/render_textured_meshes.ipynb

@@ -93,6 +93,7 @@
     "\n",
     "# Data structures and functions for rendering\n",
     "from pytorch3d.structures import Meshes\n",
+    "from pytorch3d.visualization import AxisArgs, plot_meshes\n",
     "from pytorch3d.renderer import (\n",
     "    look_at_view_transform,\n",
     "    FoVPerspectiveCameras, \n",
@@ -103,7 +104,8 @@
     "    MeshRenderer, \n",
     "    MeshRasterizer,  \n",
     "    SoftPhongShader,\n",
-    "    TexturesUV\n",
+    "    TexturesUV,\n",
+    "    TexturesVertex\n",
     ")\n",
     "\n",
     "# add path for demo utils functions \n",
@@ -555,6 +557,111 @@
     "image_grid(images.cpu().numpy(), rows=4, cols=5, rgb=True)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 7. Plotly visualization \n",
+    "If you only want to visualize a mesh, you don't really need to use a differentiable renderer - instead we support plotting of Meshes with plotly. For these Meshes, we use TexturesVertex to define a texture for the rendering.\n",
+    "`plot_meshes` creates a Plotly figure with a trace for each Meshes object. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "verts, faces_idx, _ = load_obj(obj_filename)\n",
+    "faces = faces_idx.verts_idx\n",
+    "\n",
+    "# Initialize each vertex to be white in color.\n",
+    "verts_rgb = torch.ones_like(verts)[None]  # (1, V, 3)\n",
+    "textures = TexturesVertex(verts_features=verts_rgb.to(device))\n",
+    "\n",
+    "# Create a Meshes object\n",
+    "mesh = Meshes(\n",
+    "    verts=[verts.to(device)],   \n",
+    "    faces=[faces.to(device)],\n",
+    "    textures=textures\n",
+    ")\n",
+    "\n",
+    "# Render the plotly figure\n",
+    "fig = plot_meshes(mesh)\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# use Plotly's default colors (no texture)\n",
+    "mesh = Meshes(\n",
+    "    verts=[verts.to(device)],   \n",
+    "    faces=[faces.to(device)]\n",
+    ")\n",
+    "\n",
+    "# Render the plotly figure\n",
+    "plot_meshes(mesh)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# create a batch of meshes, and offset one to prevent overlap\n",
+    "mesh_batch = Meshes(\n",
+    "    verts=[verts.to(device), (verts + 2).to(device)],   \n",
+    "    faces=[faces.to(device), faces.to(device)]\n",
+    ")\n",
+    "\n",
+    "plot_meshes(mesh_batch)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# extend the batch to have 4 meshes\n",
+    "mesh = mesh_batch.extend(2)\n",
+    "\n",
+    "# visualize the batch in different subplots, 2 per row\n",
+    "# title the subplots\n",
+    "fig = plot_meshes(mesh, in_subplots=True, ncols=2,\n",
+    "           subplot_titles = [\"cow\" + str(i) for i in range(1,5)]  # this should have a title for each subplot, titles can be \"\"\n",
+    "           )\n",
+    "# we can update the figure height and width\n",
+    "fig.update_layout(height=500, width=500)\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also modify the axis arguments and axis backgrounds."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig2 = plot_meshes(mesh_batch, xaxis={\"backgroundcolor\":\"rgb(200, 200, 230)\"},\n",
+    "                        yaxis={\"backgroundcolor\":\"rgb(230, 200, 200)\"},\n",
+    "                        zaxis={\"backgroundcolor\":\"rgb(200, 230, 200)\"}, \n",
+    "                        subplot_titles=[\"2 meshes\"],\n",
+    "                        axis_args=AxisArgs(showgrid=True))\n",
+    "fig2.show()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -562,15 +669,15 @@
     "id": "t3qphI1ElUb5"
    },
    "source": [
-    "## 7. Conclusion\n",
-    "In this tutorial we learnt how to **load** a textured mesh from an obj file, initialize a PyTorch3D datastructure called **Meshes**, set up an **Renderer** consisting of a **Rasterizer** and a **Shader**, and modify several components of the rendering pipeline. "
+    "## 8. Conclusion\n",
+    "In this tutorial we learnt how to **load** a textured mesh from an obj file, initialize a PyTorch3D datastructure called **Meshes**, set up an **Renderer** consisting of a **Rasterizer** and a **Shader**, and modify several components of the rendering pipeline. We also learned how to render Meshes in Plotly figures."
    ]
   }
  ],
  "metadata": {
   "accelerator": "GPU",
   "anp_metadata": {
-   "path": "fbsource/fbcode/vision/fair/pytorch3d/docs/tutorials/render_textured_meshes.ipynb"
+   "path": "notebooks/render_textured_meshes.ipynb"
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   "bento_stylesheets": {
    "bento/extensions/flow/main.css": true,
@@ -588,9 +695,9 @@
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   },
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-   "display_name": "intro_to_cv",
+   "display_name": "pytorch3d_etc (local)",
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-   "name": "bento_kernel_intro_to_cv"
+   "name": "pytorch3d_etc_local"
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