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Merge pull request #2265 from mikedh/feat/norm
Release: Fix Triangulation Option
2 parents e20de7e + b7609f1 commit 2c20b49

15 files changed

Lines changed: 114 additions & 98 deletions

‎Dockerfile‎

Lines changed: 3 additions & 11 deletions
Original file line numberDiff line numberDiff line change
@@ -27,16 +27,7 @@ COPY --chown=499 pyproject.toml /home/user/
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USER user
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# install trimesh into .local
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# then delete any included test directories
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# and remove Cython after all the building is complete
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# TODO
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# remove mapbox-earcut fork when this is merged:
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# https://github.com/skogler/mapbox_earcut_python/pull/15
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RUN pip install --user /home/user[easy] && \
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pip install --user --force-reinstall git+https://github.com/mikedh/mapbox_earcut_python.git && \
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find /home/user/.local -type d -name tests -prune -exec rm -rf {} \;
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RUN pip install --user /home/user[easy]
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####################################
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### Build output image most things should run on
@@ -73,7 +64,8 @@ RUN trimesh-setup --install=test,gmsh,gltf_validator,llvmpipe,binvox
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USER user
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# install things like pytest and make sure we're on Numpy 2.X
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RUN pip install .[all] && \
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# todo : imagio is forcing a downgrade of numpy 2 in-place
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RUN pip install .[all] && pip install --force-reinstall --upgrade "numpy>2" && \
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python -c "import numpy as n; assert(n.__version__.startswith('2'))"
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# check for lint problems

‎examples/colors.ipynb‎

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@@ -26,7 +26,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"m = trimesh.load('../models/machinist.XAML',process=False)"
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"m = trimesh.load(\"../models/machinist.XAML\", process=False)"
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]
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},
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{

‎examples/curvature.ipynb‎

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@@ -17,10 +17,16 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"import trimesh\n",
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"from trimesh.curvature import discrete_gaussian_curvature_measure, discrete_mean_curvature_measure, sphere_ball_intersection\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"\n",
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"import trimesh\n",
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"from trimesh.curvature import (\n",
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" discrete_gaussian_curvature_measure,\n",
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" discrete_mean_curvature_measure,\n",
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" sphere_ball_intersection,\n",
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")\n",
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"\n",
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"%matplotlib inline\n",
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"\n",
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"mesh = trimesh.creation.icosphere()"
@@ -33,8 +39,20 @@
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"outputs": [],
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"source": [
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"radii = np.linspace(0.1, 2.0, 10)\n",
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"gauss = np.array([discrete_gaussian_curvature_measure(mesh, mesh.vertices, r)/sphere_ball_intersection(1, r) for r in radii])\n",
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"mean = np.array([discrete_mean_curvature_measure(mesh, mesh.vertices, r)/sphere_ball_intersection(1, r) for r in radii])"
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"gauss = np.array(\n",
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" [\n",
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" discrete_gaussian_curvature_measure(mesh, mesh.vertices, r)\n",
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" / sphere_ball_intersection(1, r)\n",
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" for r in radii\n",
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" ]\n",
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")\n",
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"mean = np.array(\n",
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" [\n",
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" discrete_mean_curvature_measure(mesh, mesh.vertices, r)\n",
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" / sphere_ball_intersection(1, r)\n",
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" for r in radii\n",
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" ]\n",
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")"
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]
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},
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{
@@ -45,11 +63,11 @@
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"source": [
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"plt.figure()\n",
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"plt.plot(radii, gauss.mean(axis=1))\n",
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"plt.title('Gaussian Curvature')\n",
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"plt.title(\"Gaussian Curvature\")\n",
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"plt.show()\n",
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"plt.figure()\n",
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"plt.plot(radii, mean.mean(axis=1))\n",
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"plt.title('Mean Curvature')\n",
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"plt.title(\"Mean Curvature\")\n",
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"plt.show();"
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]
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},

‎examples/nearest.ipynb‎

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@@ -19,8 +19,9 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"import trimesh \n",
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"import numpy as np"
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"import numpy as np\n",
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"\n",
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"import trimesh"
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"# load a large- ish PLY model with colors \n",
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"mesh = trimesh.load('../models/cycloidal.ply') "
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"# load a large- ish PLY model with colors\n",
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"mesh = trimesh.load(\"../models/cycloidal.ply\")"
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]
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},
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{
@@ -50,10 +51,8 @@
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"outputs": [],
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"source": [
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"# find the closest point on the mesh to each random point\n",
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"(closest_points,\n",
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" distances,\n",
55-
" triangle_id) = mesh.nearest.on_surface(points)\n",
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"# distance from point to surface of mesh", "distances"
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"(closest_points, distances, triangle_id) = mesh.nearest.on_surface(points)\n",
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"# distance from point to surface of meshdistances"
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]
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},
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{
@@ -64,21 +63,19 @@
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"source": [
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"# create a PointCloud object out of each (n,3) list of points\n",
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"cloud_original = trimesh.points.PointCloud(points)\n",
67-
"cloud_close = trimesh.points.PointCloud(closest_points)\n",
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"cloud_close = trimesh.points.PointCloud(closest_points)\n",
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"\n",
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"# create a unique color for each point\n",
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"cloud_colors = np.array([trimesh.visual.random_color() for i in points])\n",
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"\n",
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"# set the colors on the random point and its nearest point to be the same\n",
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"cloud_original.vertices_color = cloud_colors\n",
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"cloud_close.vertices_color = cloud_colors\n",
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"cloud_close.vertices_color = cloud_colors\n",
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"\n",
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"# create a scene containing the mesh and two sets of points\n",
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"scene = trimesh.Scene([mesh,\n",
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" cloud_original,\n",
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" cloud_close])\n",
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"scene = trimesh.Scene([mesh, cloud_original, cloud_close])\n",
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"\n",
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"# show the scene wusing \n",
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"# show the scene wusing\n",
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"scene.show()"
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]
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}

‎examples/quick_start.ipynb‎

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@@ -18,6 +18,7 @@
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"\n",
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"import trimesh"
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]
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},
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"outputs": [],
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"source": [
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"# load a file by name or from a buffer\n",
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"mesh = trimesh.load_mesh('../models/featuretype.STL')\n",
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"mesh = trimesh.load_mesh(\"../models/featuretype.STL\")\n",
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"# to keep the raw data intact, disable any automatic processing\n",
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"#mesh = trimesh.load_mesh('../models/featuretype.STL', process=False)"
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"# mesh = trimesh.load_mesh('../models/featuretype.STL', process=False)"
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]
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},
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{
@@ -180,7 +181,11 @@
180181
"# available, and will be the minimum volume version of each\n",
181182
"# except in certain degenerate cases, where they will be no worse\n",
182183
"# than a least squares fit version of the primitive.\n",
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"(mesh.bounding_box_oriented.volume, mesh.bounding_cylinder.volume, mesh.bounding_sphere.volume)"
184+
"(\n",
185+
" mesh.bounding_box_oriented.volume,\n",
186+
" mesh.bounding_cylinder.volume,\n",
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" mesh.bounding_sphere.volume,\n",
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")"
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]
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}
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],

‎examples/ray.ipynb‎

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@@ -17,8 +17,9 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"import trimesh\n",
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"import numpy as np"
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"import numpy as np\n",
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"\n",
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"import trimesh"
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]
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},
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{
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"outputs": [],
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"source": [
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"# create some rays\n",
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"ray_origins = np.array([[0, 0, -3],\n",
42-
" [2, 2, -3]])\n",
43-
"ray_directions = np.array([[0, 0, 1],\n",
44-
" [0, 0, 1]])"
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"ray_origins = np.array([[0, 0, -3], [2, 2, -3]])\n",
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"ray_directions = np.array([[0, 0, 1], [0, 0, 1]])"
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]
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},
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{
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"source": [
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"# run the mesh- ray query\n",
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"locations, index_ray, index_tri = mesh.ray.intersects_location(\n",
65-
" ray_origins=ray_origins,\n",
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" ray_directions=ray_directions)"
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" ray_origins=ray_origins, ray_directions=ray_directions\n",
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")"
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"# the rays hit the mesh at coordinates", "locations"
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"# the rays hit the mesh at coordinateslocations"
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
84-
"# the rays with index_ray hit the triangles stored at mesh.faces[index_tri]",
85-
"len(index_ray)"
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"# the rays with index_ray hit the triangles stored at mesh.faces[index_tri]len(index_ray)"
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]
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},
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{
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9290
"outputs": [],
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"source": [
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"# stack rays into line segments for visualization as Path3D\n",
95-
"ray_visualize = trimesh.load_path(np.hstack((ray_origins,\n",
96-
" ray_origins + ray_directions*5.0)).reshape(-1, 2, 3))"
93+
"ray_visualize = trimesh.load_path(\n",
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" np.hstack((ray_origins, ray_origins + ray_directions * 5.0)).reshape(-1, 2, 3)\n",
95+
")"
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]
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},
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{
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105104
"# unmerge so viewer doesn't smooth\n",
106105
"mesh.unmerge_vertices()\n",
107106
"# make mesh white- ish\n",
108-
"mesh.visual.face_colors = [255,255,255,255]\n",
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"mesh.visual.face_colors = [255, 255, 255, 255]\n",
109108
"mesh.visual.face_colors[index_tri] = [255, 0, 0, 255]"
110109
]
111110
},
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116115
"outputs": [],
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"source": [
118117
"# create a visualization scene with rays, hits, and mesh\n",
119-
"scene = trimesh.Scene([mesh,\n",
120-
" ray_visualize])"
118+
"scene = trimesh.Scene([mesh, ray_visualize])"
121119
]
122120
},
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{

‎examples/save_image.ipynb‎

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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import trimesh\n",
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"import math"
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"import math\n",
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"\n",
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"import trimesh"
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]
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},
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{
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3232
"outputs": [],
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"source": [
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"# load a file by name\n",
35-
"mesh = trimesh.load_mesh('../models/featuretype.STL')"
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"mesh = trimesh.load_mesh(\"../models/featuretype.STL\")"
3636
]
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},
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{
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9292
" math.radians(45),\n",
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" math.radians(45),\n",
9494
" \"ryxz\",\n",
95-
" )"
95+
")"
9696
]
9797
},
9898
{
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102102
"metadata": {},
103103
"outputs": [],
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"source": [
105-
"# Get camera transform to look at geometry with isometric view \n",
105+
"# Get camera transform to look at geometry with isometric view\n",
106106
"t_r = scene.camera.look_at(corners, rotation=r_e)"
107107
]
108108
},
@@ -136,7 +136,7 @@
136136
"outputs": [],
137137
"source": [
138138
"# Write the bytes to file\n",
139-
"with open('../models/featuretype.png', \"wb\") as f:\n",
139+
"with open(\"../models/featuretype.png\", \"wb\") as f:\n",
140140
" f.write(png)\n",
141141
" f.close()"
142142
]

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