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Merge pull request #443 from K3D-tools/devel
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2.16.1
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@artur-trzesiok
artur-trzesiok authored Jan 6, 2024
2 parents d520079 + bc185b9 commit 46bec85
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26 changes: 1 addition & 25 deletions .github/workflows/test.yml
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name: Build and Test
name: Test

on: [push, pull_request]

jobs:
build_wheels:
name: Build wheels on ${{ matrix.os }}
runs-on: ubuntu-22.04

steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v3
- name: Install dependencies
run: python -m pip install --upgrade pip setuptools wheel build
- name: Use Node.js
uses: actions/setup-node@v3
with:
node-version: "16"
- name: Build wheels
run: python -m build .

- uses: actions/upload-artifact@v3
with:
name: k3d_wheel
path: ./dist/k3d*.whl
- uses: actions/upload-artifact@v3
with:
name: k3d_sdist
path: ./dist/k3d*.tar.gz
test:
name: Run pytest on ${{ matrix.os }}
runs-on: ${{ matrix.os }}
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304 changes: 304 additions & 0 deletions examples/point_cloud_advanced_compression_in_html.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from k3d.helpers import download\n",
"from pyunpack import Archive\n",
"import os\n",
"from IPython.display import IFrame\n",
"\n",
"filename = download('http://www.semantic3d.net/data/point-clouds/testing1/stgallencathedral_station1_intensity_rgb.7z')\n",
"Archive(filename).extractall('./')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import csv\n",
"import numpy as np \n",
"\n",
"data = None\n",
"\n",
"with open(filename.replace('.7z', '.txt'), mode='r') as csv_file:\n",
" csv_reader = csv.reader(csv_file, delimiter=' ') \n",
" data = np.array(list(csv_reader), dtype=np.float32)\n",
"\n",
"# compute color in hex format\n",
"data[:, 4] = np.sum(data[:, 4:7].astype(np.uint32) * np.array([1, 256, 256 ** 2]), axis=1) \n",
"data = data[:, 0:5]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"positions = data[::10, 0:3]\n",
"colors1 = data[::10, 4].astype(np.uint32)\n",
"colors2 = np.clip(colors1.view(np.uint8) * 1.5, 0, 255).astype(np.uint8).view('uint32')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"positions.shape, colors1.shape, colors2.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"cam_pos = [5.251483149143791,\n",
" -7.92683507646606,\n",
" 3.144285796928443,\n",
" -2.470283607444292,\n",
" 3.6558150584160503,\n",
" 2.3721091212696286,\n",
" 0,\n",
" 0,\n",
" 1]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import time\n",
"import json\n",
"import k3d\n",
"import ipywidgets as widgets\n",
"\n",
"plot = k3d.plot()\n",
"plot += k3d.points(positions, colors1, point_size=0.2, shader=\"flat\") \n",
"plot += k3d.points(positions, colors2, point_size=0.2, shader=\"flat\") \n",
"plot.display()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plot.camera = cam_pos"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"with open(\"point_cloud_full.html\", \"w\") as f:\n",
" f.write(plot.get_snapshot(additional_js_code=\"\"\"\n",
" let json = K3DInstance.getWorld().ObjectsListJson; \n",
" let active = Object.keys(json)[0];\n",
" \n",
" setInterval(() => {\n",
" let newActive;\n",
" \n",
" Object.keys(json).forEach(function (id) {\n",
" if (active === id) {\n",
" json[id].opacity = 0;\n",
" K3DInstance.reload(json[id], {opacity: 0}); \n",
" } else {\n",
" json[id].opacity = 1;\n",
" K3DInstance.reload(json[id], {opacity: 1});\n",
" newActive = id;\n",
" } \n",
" });\n",
" \n",
" active = newActive;\n",
" \n",
" }, 2000);\n",
" \n",
" \n",
" \"\"\"))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# size in html\n",
"os.stat(\"point_cloud_full.html\").st_size / 1024 / 1024 # size in MB"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"IFrame('point_cloud_full.html', width=900, height=350)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Advanced approach"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import time\n",
"import json\n",
"import k3d\n",
"import ipywidgets as widgets\n",
"\n",
"plot2 = k3d.plot()\n",
"\n",
"positions_placeholder = positions.copy()\n",
"positions_placeholder.fill(0.0) # filling with one value will boost compression ratio\n",
"\n",
"plot2 += k3d.points(positions, colors1, point_size=0.2, shader=\"flat\", name=\"main\") \n",
"plot2 += k3d.points(positions_placeholder, colors2, point_size=0.2, shader=\"flat\", name=\"second\") \n",
"\n",
"plot2.display()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plot2.camera = cam_pos"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"with open(\"point_cloud_advanced.html\", \"w\") as f:\n",
" f.write(plot2.get_snapshot(additional_js_code=\"\"\"\n",
" let json = K3DInstance.getWorld().ObjectsListJson; \n",
" let active = Object.keys(json)[0];\n",
" let positions = null;\n",
" \n",
" // search for main and save positions from it\n",
" Object.keys(json).forEach(function (id) {\n",
" if (json[id].name === 'main') {\n",
" positions = json[id].positions.data;\n",
" }\n",
" });\n",
" \n",
" // search for second and update positions\n",
" Object.keys(json).forEach(function (id) {\n",
" if (json[id].name === 'second') {\n",
" json[id].positions.data.set(positions);\n",
" K3DInstance.reload(json[id], {positions: json[id].positions}); \n",
" }\n",
" });\n",
" \n",
" \n",
" // like before\n",
" \n",
" setInterval(() => {\n",
" let json = K3DInstance.getWorld().ObjectsListJson;\n",
" let newActive;\n",
" \n",
" Object.keys(json).forEach(function (id) {\n",
" if (active === id) {\n",
" json[id].opacity = 0;\n",
" K3DInstance.reload(json[id], {opacity: 0}); \n",
" } else {\n",
" json[id].opacity = 1;\n",
" K3DInstance.reload(json[id], {opacity: 1});\n",
" newActive = id;\n",
" } \n",
" });\n",
" \n",
" active = newActive;\n",
" \n",
" }, 2000);\n",
" \n",
" \n",
" \"\"\"))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# size in html\n",
"os.stat(\"point_cloud_advanced.html\").st_size / 1024 / 1024 # size in MB"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"IFrame('point_cloud_advanced.html', width=900, height=350)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# ratio\n",
"os.stat(\"point_cloud_advanced.html\").st_size / os.stat(\"point_cloud_full.html\").st_size"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# ratio cannot be 0.5 because we pass information about each points color"
]
}
],
"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": 4
}
2 changes: 1 addition & 1 deletion js/package.json
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{
"name": "k3d",
"version": "2.16.0",
"version": "2.16.1",
"description": "3D visualization library",
"author": "k3d team",
"main": "src/index.js",
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4 changes: 4 additions & 0 deletions js/src/core/lib/headless.html
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Expand Up @@ -162,10 +162,14 @@
if (promises.length > 0) {
Promise.all(promises).then(function () {
window.refreshed = true;
}).catch(function(error) {
console.error(error);
});
} else {
window.refreshed = true;
}
} else {
console.error('k3dRefresh', req.response);
}
}
});
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