Fix for #7149 + readme for docker on Windows + fixing typos (#7150)

joseph-sch · ssheorey · web-flow · commit e2d2bd040012 · 2025-04-02T16:11:58.000-07:00
* A readme for building using docker build script on Windows using WSL
* Instructions for building using Docker and WSL
* Fix typo in argument of TriangleMesh.create_mobius
* Fix typos in comments and strings
* Fix another docstring
---------
Co-authored-by: Sameer Sheorey &lt;41028320+ssheorey@users.noreply.github.com&gt;
diff --git a/cpp/open3d/geometry/TetraMesh.h b/cpp/open3d/geometry/TetraMesh.h
@@ -49,7 +49,7 @@ class TetraMesh : public MeshBase {
     TetraMesh &operator+=(const TetraMesh &mesh);
     TetraMesh operator+(const TetraMesh &mesh) const;
 
-    /// \brief Function that removes duplicated verties, i.e., vertices that
+    /// \brief Function that removes duplicated vertices, i.e., vertices that
     /// have identical coordinates.
     TetraMesh &RemoveDuplicatedVertices();
 
diff --git a/cpp/open3d/geometry/TriangleMesh.h b/cpp/open3d/geometry/TriangleMesh.h
@@ -116,7 +116,7 @@ class TriangleMesh : public MeshBase {
     /// needed.
     TriangleMesh &ComputeAdjacencyList();
 
-    /// \brief Function that removes duplicated verties, i.e., vertices that
+    /// \brief Function that removes duplicated vertices, i.e., vertices that
     /// have identical coordinates.
     TriangleMesh &RemoveDuplicatedVertices();
 
@@ -560,15 +560,15 @@ class TriangleMesh : public MeshBase {
     /// Factory function to create a tetrahedron mesh (trianglemeshfactory.cpp).
     /// the mesh centroid will be at (0,0,0) and \p radius defines the
     /// distance from the center to the mesh vertices.
-    /// \param radius defines the distance from centroid to mesh vetices.
+    /// \param radius defines the distance from centroid to mesh vertices.
     /// \param create_uv_map add default UV map to the mesh.
     static std::shared_ptr<TriangleMesh> CreateTetrahedron(
             double radius = 1.0, bool create_uv_map = false);
 
     /// Factory function to create an octahedron mesh (trianglemeshfactory.cpp).
     /// the mesh centroid will be at (0,0,0) and \p radius defines the
     /// distance from the center to the mesh vertices.
-    /// \param radius defines the distance from centroid to mesh vetices.
+    /// \param radius defines the distance from centroid to mesh vertices.
     /// \param create_uv_map add default UV map to the mesh.
     static std::shared_ptr<TriangleMesh> CreateOctahedron(
             double radius = 1.0, bool create_uv_map = false);
diff --git a/cpp/open3d/t/geometry/PointCloud.h b/cpp/open3d/t/geometry/PointCloud.h
@@ -710,7 +710,7 @@ class PointCloud : public Geometry, public DrawableGeometry {
     /// surface points from the first point cloud that have the second point
     /// cloud points within the threshold radius, while Precision is the
     /// percentage of points from the second point cloud that have the first
-    /// point cloud points within the threhold radius.
+    /// point cloud points within the threshold radius.
 
     /// \f{eqnarray*}{
     ///   \text{Chamfer Distance: } d_{CD}(X,Y) &=& \frac{1}{|X|}\sum_{i \in X}
diff --git a/cpp/open3d/t/geometry/TriangleMesh.h b/cpp/open3d/t/geometry/TriangleMesh.h
@@ -405,7 +405,7 @@ class TriangleMesh : public Geometry, public DrawableGeometry {
     /// Create a tetrahedron triangle mesh. The centroid of the mesh will be
     /// placed at (0, 0, 0) and the vertices have a distance of radius to the
     /// center.
-    /// \param radius defines the distance from centroid to mesh vetices.
+    /// \param radius defines the distance from centroid to mesh vertices.
     /// \param float_dtype Float32 or Float64, used to store floating point
     /// values, e.g. vertices, normals, colors.
     /// \param int_dtype Int32 or Int64, used to store index values, e.g.
@@ -420,7 +420,7 @@ class TriangleMesh : public Geometry, public DrawableGeometry {
     /// Create a octahedron triangle mesh. The centroid of the mesh will be
     /// placed at (0, 0, 0) and the vertices have a distance of radius to the
     /// center.
-    /// \param radius defines the distance from centroid to mesh vetices.
+    /// \param radius defines the distance from centroid to mesh vertices.
     /// \param float_dtype Float32 or Float64, used to store floating point
     /// values, e.g. vertices, normals, colors.
     /// \param int_dtype Int32 or Int64, used to store index values, e.g.
@@ -435,7 +435,7 @@ class TriangleMesh : public Geometry, public DrawableGeometry {
     /// Create a icosahedron triangle mesh. The centroid of the mesh will be
     /// placed at (0, 0, 0) and the vertices have a distance of radius to the
     /// center.
-    /// \param radius defines the distance from centroid to mesh vetices.
+    /// \param radius defines the distance from centroid to mesh vertices.
     /// \param float_dtype Float32 or Float64, used to store floating point
     /// values, e.g. vertices, normals, colors.
     /// \param int_dtype Int32 or Int64, used to store index values, e.g.
@@ -1063,7 +1063,7 @@ class TriangleMesh : public Geometry, public DrawableGeometry {
     /// percentage of surface points from the first mesh that have the second
     /// mesh within the threshold radius, while Precision is the percentage of
     /// sampled points from the second mesh that have the first mesh surface
-    /// within the threhold radius.
+    /// within the threshold radius.
 
     /// \f{eqnarray*}{
     ///   \text{Chamfer Distance: } d_{CD}(X,Y) &=& \frac{1}{|X|}\sum_{i \in X}
diff --git a/cpp/pybind/geometry/trianglemesh.cpp b/cpp/pybind/geometry/trianglemesh.cpp
@@ -421,7 +421,7 @@ void pybind_trianglemesh_definitions(py::module &m) {
             .def_static("create_mobius", &TriangleMesh::CreateMobius,
                         "Factory function to create a Mobius strip.",
                         "length_split"_a = 70, "width_split"_a = 15,
-                        "twists"_a = 1, "raidus"_a = 1, "flatness"_a = 1,
+                        "twists"_a = 1, "radius"_a = 1, "flatness"_a = 1,
                         "width"_a = 1, "scale"_a = 1)
             .def_readwrite("vertices", &TriangleMesh::vertices_,
                            "``float64`` array of shape ``(num_vertices, 3)``, "
@@ -710,15 +710,15 @@ void pybind_trianglemesh_definitions(py::module &m) {
              {"map_texture_to_each_face", "Map entire texture to each face."}});
     docstring::ClassMethodDocInject(
             m, "TriangleMesh", "create_tetrahedron",
-            {{"radius", "Distance from centroid to mesh vetices."},
+            {{"radius", "Distance from centroid to mesh vertices."},
              {"create_uv_map", "Add default uv map to the mesh."}});
     docstring::ClassMethodDocInject(
             m, "TriangleMesh", "create_octahedron",
-            {{"radius", "Distance from centroid to mesh vetices."},
+            {{"radius", "Distance from centroid to mesh vertices."},
              {"create_uv_map", "Add default uv map to the mesh."}});
     docstring::ClassMethodDocInject(
             m, "TriangleMesh", "create_icosahedron",
-            {{"radius", "Distance from centroid to mesh vetices."},
+            {{"radius", "Distance from centroid to mesh vertices."},
              {"create_uv_map", "Add default uv map to the mesh."}});
     docstring::ClassMethodDocInject(
             m, "TriangleMesh", "create_sphere",
diff --git a/cpp/pybind/t/geometry/pointcloud.cpp b/cpp/pybind/t/geometry/pointcloud.cpp
@@ -765,7 +765,7 @@ the partition id for each point.
 
 Example:
 
-    This code computes parititions a point cloud such that each partition
+    This code computes partitions of a point cloud such that each partition
     contains at most 20 points::
 
         import open3d as o3d
@@ -780,16 +780,16 @@ the partition id for each point.
 
     pointcloud.def("compute_metrics", &PointCloud::ComputeMetrics, "pcd2"_a,
                    "metrics"_a, "params"_a,
-                   R"(Compute various metrics between two point clouds. 
-            
-Currently, Chamfer distance, Hausdorff distance and F-Score `[Knapitsch2017] <../tutorial/reference.html#Knapitsch2017>`_ are supported. 
-The Chamfer distance is the sum of the mean distance to the nearest neighbor 
+                   R"(Compute various metrics between two point clouds.
+
+Currently, Chamfer distance, Hausdorff distance and F-Score `[Knapitsch2017] <../tutorial/reference.html#Knapitsch2017>`_ are supported.
+The Chamfer distance is the sum of the mean distance to the nearest neighbor
 from the points of the first point cloud to the second point cloud. The F-Score
-at a fixed threshold radius is the harmonic mean of the Precision and Recall. 
-Recall is the percentage of surface points from the first point cloud that have 
-the second point cloud points within the threshold radius, while Precision is 
-the percentage of points from the second point cloud that have the first point 
-cloud points within the threhold radius.
+at a fixed threshold radius is the harmonic mean of the Precision and Recall.
+Recall is the percentage of surface points from the first point cloud that have
+the second point cloud points within the threshold radius, while Precision is
+the percentage of points from the second point cloud that have the first point
+cloud points within the threshold radius.
 
 .. math::
     :nowrap:
diff --git a/cpp/pybind/t/geometry/trianglemesh.cpp b/cpp/pybind/t/geometry/trianglemesh.cpp
@@ -408,7 +408,7 @@ This example shows how to create a hemisphere from a sphere::
                         "device"_a = core::Device("CPU:0"))
             .def_static("create_mobius", &TriangleMesh::CreateMobius,
                         "Create a Mobius strip.", "length_split"_a = 70,
-                        "width_split"_a = 15, "twists"_a = 1, "raidus"_a = 1,
+                        "width_split"_a = 15, "twists"_a = 1, "radius"_a = 1,
                         "flatness"_a = 1, "width"_a = 1, "scale"_a = 1,
                         "float_dtype"_a = core::Float32,
                         "int_dtype"_a = core::Int64,
@@ -431,19 +431,19 @@ This example shows how to create a hemisphere from a sphere::
              {"device", "Device of the create sphere."}});
     docstring::ClassMethodDocInject(
             m, "TriangleMesh", "create_tetrahedron",
-            {{"radius", "Distance from centroid to mesh vetices."},
+            {{"radius", "Distance from centroid to mesh vertices."},
              {"float_dtype", "Float_dtype, Float32 or Float64."},
              {"int_dtype", "Int_dtype, Int32 or Int64."},
              {"device", "Device of the create tetrahedron."}});
     docstring::ClassMethodDocInject(
             m, "TriangleMesh", "create_octahedron",
-            {{"radius", "Distance from centroid to mesh vetices."},
+            {{"radius", "Distance from centroid to mesh vertices."},
              {"float_dtype", "Float_dtype, Float32 or Float64."},
              {"int_dtype", "Int_dtype, Int32 or Int64."},
              {"device", "Device of the create octahedron."}});
     docstring::ClassMethodDocInject(
             m, "TriangleMesh", "create_icosahedron",
-            {{"radius", "Distance from centroid to mesh vetices."},
+            {{"radius", "Distance from centroid to mesh vertices."},
              {"float_dtype", "Float_dtype, Float32 or Float64."},
              {"int_dtype", "Int_dtype, Int32 or Int64."},
              {"device", "Device of the create octahedron."}});
@@ -545,7 +545,7 @@ This example shows how to create a hemisphere from a sphere::
     Text as triangle mesh.
 
 Example:
-    This shows how to simplifify the Stanford Bunny mesh::
+    This shows how to simplify the Stanford Bunny mesh::
 
         import open3d as o3d
 
@@ -635,7 +635,7 @@ This function always uses the CPU device.
     Simplified TriangleMesh.
 
 Example:
-    This shows how to simplifify the Stanford Bunny mesh::
+    This shows how to simplify the Stanford Bunny mesh::
 
         bunny = o3d.data.BunnyMesh()
         mesh = o3d.t.geometry.TriangleMesh.from_legacy(o3d.io.read_triangle_mesh(bunny.path))
@@ -662,7 +662,7 @@ This function always uses the CPU device.
     The mesh describing the union volume.
 
 Example:
-    This copmutes the union of a sphere and a cube::
+    This computes the union of a sphere and a cube::
 
         box = o3d.geometry.TriangleMesh.create_box()
         box = o3d.t.geometry.TriangleMesh.from_legacy(box)
@@ -693,7 +693,7 @@ This function always uses the CPU device.
     The mesh describing the intersection volume.
 
 Example:
-    This copmutes the intersection of a sphere and a cube::
+    This computes the intersection of a sphere and a cube::
 
         box = o3d.geometry.TriangleMesh.create_box()
         box = o3d.t.geometry.TriangleMesh.from_legacy(box)
@@ -1156,8 +1156,8 @@ the sampled surface points of the first mesh to the second mesh and vice versa.
 The F-Score at the fixed threshold radius is the harmonic mean of the Precision
 and Recall. Recall is the percentage of surface points from the first mesh that
 have the second mesh within the threshold radius, while Precision is the
-percentage of sampled points from the second mesh that have the first mesh
-surface within the threhold radius.
+percentage of sampled points from the second mesh that have the first mesh 
+surface within the threshold radius.
 
 .. math::
     :nowrap:
diff --git a/cpp/tests/core/FixedRadiusIndex.cpp b/cpp/tests/core/FixedRadiusIndex.cpp
@@ -81,7 +81,7 @@ TEST(FixedRadiusIndex, SearchRadius) {
     float radius = 0.1;
     core::nns::FixedRadiusIndex index32(dataset_points, radius, core::Int32);
 
-    // if raidus == 0.1
+    // if radius == 0.1
     core::Tensor indices, distances, neighbors_row_splits;
     core::SizeVector shape{2};
     gt_indices = core::Tensor::Init<int32_t>({1, 4}, device);
@@ -102,7 +102,7 @@ TEST(FixedRadiusIndex, SearchRadius) {
     // Set up index.
     core::nns::FixedRadiusIndex index64(dataset_points, radius, core::Int64);
 
-    // if raidus == 0.1
+    // if radius == 0.1
     shape = core::SizeVector{2};
     gt_indices = core::Tensor::Init<int64_t>({1, 4}, device);
     gt_neighbors_row_splits = gt_neighbors_row_splits.To(core::Int64);
@@ -324,7 +324,7 @@ TEST(FixedRadiusIndex, SearchHybrid) {
     int max_knn = 3;
     core::nns::FixedRadiusIndex index32(dataset_points, radius, core::Int32);
 
-    // if raidus == 0.1
+    // if radius == 0.1
     core::Tensor indices, distances, counts;
     core::SizeVector shape{1, 3};
     core::SizeVector shape_counts{1};
@@ -347,7 +347,7 @@ TEST(FixedRadiusIndex, SearchHybrid) {
     // Set up index.
     core::nns::FixedRadiusIndex index64(dataset_points, radius, core::Int64);
 
-    // if raidus == 0.1
+    // if radius == 0.1
     gt_indices = core::Tensor::Init<int64_t>({{1, 4, -1}}, device);
     gt_counts = core::Tensor::Init<int64_t>({2}, device);
 
diff --git a/cpp/tests/core/NearestNeighborSearch.cpp b/cpp/tests/core/NearestNeighborSearch.cpp
@@ -191,7 +191,7 @@ TEST_P(NNSPermuteDevices, FixedRadiusSearch) {
                      std::runtime_error);
     }
 
-    // If raidus == 0.1.
+    // If radius == 0.1.
     nns32.FixedRadiusIndex(0.1);
     std::tuple<core::Tensor, core::Tensor, core::Tensor> result;
     core::SizeVector shape{2};
@@ -223,7 +223,7 @@ TEST_P(NNSPermuteDevices, FixedRadiusSearch) {
                      std::runtime_error);
     }
 
-    // If raidus == 0.1.
+    // If radius == 0.1.
     nns64.FixedRadiusIndex(0.1);
     gt_indices = core::Tensor::Init<int64_t>({1, 4}, device);
     gt_distances = core::Tensor::Init<double>({0.00626358, 0.00747938}, device);
diff --git a/docker/README.md b/docker/README.md
@@ -1,5 +1,8 @@
 # Open3D Docker
 
+This README covers, first, dependencies and instructions for building Linux, then those
+for Windows.
+
 ## Dependencies
 
 ### Docker dependencies
@@ -66,3 +69,80 @@ cd docker
 ```
 
 See `./docker_build.sh` and `./docker_test.sh` for all available options.
+
+## Building for Linux under Windows
+
+You can build and test Open3D for Linux in a Docker container under Windows using the provided scripts thanks to **[Docker Desktop for Windows](https://docs.docker.com/desktop/setup/install/windows-install/)** and **[WSL](https://learn.microsoft.com/en-us/windows/wsl/about)**.
+
+This guide walks you through installing Docker Desktop, setting up Windows Subsystem for Linux (WSL), configuring Docker integration with WSL, and building Open3D for Linux including its documentation and the Python wheel, and testing it, using the provided scripts (respectively `docker_build.sh` and `docker_test.sh`).
+
+### Step 1: Install Docker Desktop
+
+1. **Download and Install**: [Download Docker Desktop](https://www.docker.com/products/docker-desktop) and follow the on-screen prompts to install.
+2. **Launch Docker Desktop**: After installation, open Docker Desktop to ensure it is running.
+
+### Step 2: Install and Set Up WSL
+
+1. **Enable WSL**: Open PowerShell as Administrator and install WSL:
+
+   ```powershell
+   wsl --install
+   ```
+
+2. **Install a Linux Distribution** (e.g., Ubuntu-24.04):
+
+   ```powershell
+   wsl --install -d Ubuntu-24.04
+   ```
+
+3. **Restart** your system if prompted.
+
+### Step 3: Enable Docker Integration with WSL
+
+1. **Open Docker Desktop**.
+2. **Go to Settings** > **Resources** > **WSL Integration**.
+3. **Enable Integration** for your Linux distribution (e.g., Ubuntu-24.04).
+4. If necessary, **restart Docker Desktop** to apply the changes.
+
+### Step 4: Clone and check out Open3D repository
+
+1. **Open a terminal** within WSL.
+2. **Clone and check out** Open3D repository into the folder of your choice:
+
+   ```bash
+   git clone https://github.com/isl-org/Open3D /path/to/Open3D
+   ```
+
+### Step 5: Build Open3D for Linux in WSL using the provided script
+
+1. **Open your WSL terminal**.
+2. **Navigate** to the Docker folder in the Open3D repository:
+
+   ```bash
+   cd /path/to/Open3D/docker
+   ```
+
+3. **Disable PyTorch and TensorFlow ops** if not needed:
+
+   ```bash
+   export BUILD_PYTORCH_OPS=OFF
+   export BUILD_TENSORFLOW_OPS=OFF
+   ```
+
+4. **Run the Docker build script**:
+
+   E.g.:
+
+   ```bash
+   ./docker_build.sh openblas-amd64-py312
+   ```
+
+   Check the log of the build. After the build completes, you will have an Open3D Docker image ready to use, and the artifacts (binaries, documentation and Python package) will have been copied back to the host.
+
+5. **Run tests within the built Docker image**:
+
+   E.g.:
+
+   ```bash
+   ./docker_test.sh openblas-amd64-py312
+   ```
diff --git a/docs/docker.in.rst b/docs/docker.in.rst
diff --git a/examples/cpp/TrimMeshBasedOnPointCloud.cpp b/examples/cpp/TrimMeshBasedOnPointCloud.cpp
diff --git a/examples/python/visualization/online_processing.py b/examples/python/visualization/online_processing.py
diff --git a/examples/python/visualization/tensorboard_pytorch.py b/examples/python/visualization/tensorboard_pytorch.py
diff --git a/examples/python/visualization/tensorboard_tensorflow.py b/examples/python/visualization/tensorboard_tensorflow.py
