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Mg/examples readme #47

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353004a
example notebooks added
MargrietGroenendijk Aug 31, 2022
b2e5030
examples added to readme
MargrietGroenendijk Aug 31, 2022
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local dev description added
MargrietGroenendijk Aug 31, 2022
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45 changes: 23 additions & 22 deletions README.md
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Expand Up @@ -65,34 +65,36 @@ of those flags here.

#### TypeScript

If you use JupyterLab to develop then you can watch the source directory and run JupyterLab at the same time in different
terminals to watch for changes in the extension's source and automatically rebuild the widget.
The TypeScript code for the visualizations can be found in the [TileDB-Viz](https://github.com/TileDB-Inc/TileDB-Viz) package. After making changes in TileDB-Viz build the package with:

```bash
# Watch the source directory in one terminal, automatically rebuilding when needed
yarn run watch
# Run JupyterLab in another terminal
jupyter lab
```
`yarn build`

After a change wait for the build to finish and then refresh your browser and the changes should take effect.
To then see these changes in TileDB-PyBabylonJS run:

To add a TypeScript package use [yarn](https://classic.yarnpkg.com/lang/en/docs/cli/add/):
`yarn add file:/path/to/TileDB-Viz/packages/core`

```bash
yarn add <package-name>
yarn add --dev <dev-package-name>
```
`yarn build`

And restart the notebook kernel.

#### Python

If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.
When you make a change to the Python code rebuild the package and restart the notebook kernel to see your changes.

## Usage

Jupyter notebooks are provided in the [Examples](https://github.com/TileDB-Inc/TileDB-PyBabylonJS/tree/main/examples).
### Point clouds

Jupyter notebooks are provided in the [Examples folder](https://github.com/TileDB-Inc/TileDB-PyBabylonJS/tree/main/examples) for the following visualizations:

Create a default visualization from a local sparse array containing LiDAR data by specifying the bounding box (`bbox`) of the slice of the data in the array uri:
* [Point cloud](/examples/point_cloud.ipynb)
* [Point cloud with a time slider](/examples/point-cloud-time.ipynb)
* [Point cloud with a classes slider](/examples/point-cloud-classes.ipynb)
* [Point cloud with a Mapbox base map](/examples/point-cloud-topo.ipynb)
* [Point cloud with gltf models](/examples/point-cloud-gltf.ipynb)
* [MBRS of a point cloud](/examples/mbrs.ipynb)

Display a point cloud visualization from a local sparse array by specifying the bounding box of a slice of the data:

```python
from pybabylonjs import Show as show
Expand All @@ -103,14 +105,13 @@ bbox = {
'Z': [406.14, 615.26]
}

lidar_array = "autzen-classified"

show.point_cloud(source="local",
mode="default",
uri="./data/autzen",
bbox=bbox)
uri=lidar_array,
bbox = bbox)
```

This creates an interactive visualization in a notebook widget of which the below is a screenshot:

<img src="examples/pointcloud.png" width="400" height="300" />

To add a slider over `GpsTime` change the `mode` to `time`:
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13 changes: 1 addition & 12 deletions examples/mbrs.ipynb
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Expand Up @@ -9,21 +9,10 @@
"source": [
"import os\n",
"import pdal\n",
"import pybabylonjs\n",
"from pybabylonjs import Show as show\n",
"import tiledb"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ee8f4ea7-1b51-43d9-ab4d-189149f40831",
"metadata": {},
"outputs": [],
"source": [
"pybabylonjs.__version__"
]
},
{
"cell_type": "markdown",
"id": "376c7606-efde-45b5-b512-39b6987fbbf2",
Expand Down Expand Up @@ -73,7 +62,7 @@
"id": "8fce1435-d6b6-4a9d-b961-c36416375a0e",
"metadata": {},
"source": [
"### MBRS\n",
"### MBRS visualization\n",
"\n",
"Detailed information about the fragments in the array is read with:"
]
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207 changes: 207 additions & 0 deletions examples/point-cloud-classes.ipynb
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@@ -0,0 +1,207 @@
{
"cells": [
{
"cell_type": "markdown",
"id": "d4f53ca1-2726-4c0c-af0b-d39831237087",
"metadata": {},
"source": [
"# Point Cloud Data Visualization with a classes slider\n",
"\n",
"* Download point cloud data\n",
"* Create a sparse TileDB array\n",
"* Visualize the point cloud with a classes slider\n",
"* Customize with optional parameters"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c33b9bc9-cb24-4064-b8ec-61b1b332a266",
"metadata": {},
"outputs": [],
"source": [
"import requests\n",
"\n",
"import pdal\n",
"from pybabylonjs import Show as show\n",
"import tiledb"
]
},
{
"cell_type": "markdown",
"id": "fb67c477-5b04-4fd8-bec7-a286e7ae92a2",
"metadata": {},
"source": [
"## Optional: create a sparse TileDB array from a LAZ file"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f9eb5905-32a5-49e6-9b96-d89a701f91f9",
"metadata": {},
"outputs": [],
"source": [
"!wget -nc \"https://github.com/PDAL/data/blob/master/autzen/autzen-classified.laz?raw=true\" -O \"autzen-classified.laz\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d878a610-ad6f-4796-bf25-1c2f1c4d31c9",
"metadata": {},
"outputs": [],
"source": [
"pipeline = (\n",
" pdal.Reader(\"autzen-classified.laz\") |\n",
" pdal.Filter.stats() |\n",
" pdal.Writer.tiledb(array_name=\"autzen-classified\",chunk_size=100000)\n",
")\n",
"\n",
"count = pipeline.execute() "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "77cd7fd4-9e77-4307-bb7a-c828a9395530",
"metadata": {},
"outputs": [],
"source": [
"lidar_array = \"autzen-classified\""
]
},
{
"cell_type": "markdown",
"id": "300faf9b-716e-4c3c-af00-86d9cf118b39",
"metadata": {},
"source": [
"To load and display a slice of the data a bounding box with the minimum and maximum values of X, Y and Z are needed:"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7aa48a9d-9aba-4919-8ed6-3fea268b5bf4",
"metadata": {},
"outputs": [],
"source": [
"bbox = {\n",
" 'X': [636800, 637800],\n",
" 'Y': [851000, 853000],\n",
" 'Z': [406.14, 615.26]\n",
"}"
]
},
{
"cell_type": "markdown",
"id": "e179da13-10d4-42c6-ad8e-7850339eee2e",
"metadata": {},
"source": [
"### Visualize the point cloud with a classes slider\n",
"\n",
"*The below example loads the data from a local array, but a time slider can be added to point clouds from all data sources: `local`, `cloud` and `dict`.*\n",
"\n",
"Point cloud data from the local array can be loaded and displayed with the below, where `uri` is the location of the array:"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "29b8b806-b785-4784-a802-d5d7d735a12a",
"metadata": {},
"outputs": [],
"source": [
"show.point_cloud(source=\"local\",\n",
" mode=\"default\",\n",
" uri=lidar_array,\n",
" bbox = bbox)"
]
},
{
"cell_type": "markdown",
"id": "e06eaa47-7277-419f-b204-69c8418628ee",
"metadata": {},
"source": [
"To add a time slider change the mode from `default` to `classes` and add the `classes` variable that contains the names for each class. Also make sure there is an attribute `Classification` in the array:"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "95fc9ca9-19b5-4872-9369-3473bd286442",
"metadata": {},
"outputs": [],
"source": [
"classes = {\n",
" 'numbers': [0,2,5,6,9,15,17,19,64,65,66,67,68,69,70,71,72,73,74,75,76,77],\n",
" 'names': ['None','Ground','Vegetation','Building','Water','Transmission Tower',\n",
" 'Bridge Deck','Overhead Structure','Wire','Car','Truck','Boat',\n",
" 'Barrier','Railroad car','Elevated Walkway','Covered Walkway',\n",
" 'Pier/Dock','Fence','Tower','Crane','Silo/Storage Tank','Bridge Structure']\n",
"}\n",
"\n",
"show.point_cloud(source=\"local\",\n",
" mode=\"classes\",\n",
" uri=lidar_array,\n",
" bbox = bbox,\n",
" classes=classes)"
]
},
{
"cell_type": "markdown",
"id": "435491c9-1093-4c6a-b67f-6f35047e7b15",
"metadata": {},
"source": [
"## Customize with optional parameters"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c54a3e7a-7edf-4412-a018-b570481f9381",
"metadata": {},
"outputs": [],
"source": [
"show.point_cloud(source=\"local\",\n",
" mode=\"classes\",\n",
" uri=lidar_array,\n",
" bbox = bbox,\n",
" classes=classes,\n",
" width=1200,\n",
" height=800,\n",
" z_scale=1.5,\n",
" color_scheme=\"blue\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3f29c476-0dfa-43e8-8eb2-9b680a04da4d",
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.7.10"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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