Add image generated example

docs/maplibre/add_image_generated.ipynb

@@ -0,0 +1,148 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "[![image](https://jupyterlite.rtfd.io/en/latest/_static/badge.svg)](https://demo.leafmap.org/lab/index.html?path=maplibre/add_image_generated.ipynb)\n",
+    "[![image](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/opengeos/leafmap/blob/master/docs/maplibre/add_image_generated.ipynb)\n",
+    "[![image](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/opengeos/leafmap/HEAD)\n",
+    "\n",
+    "**Add a generated icon to the map**\n",
+    "\n",
+    "This source code of this example is adapted from the MapLibre GL JS example - [Add a generated icon to the map](https://maplibre.org/maplibre-gl-js/docs/examples/add-image-generated).\n",
+    "\n",
+    "Uncomment the following line to install [leafmap](https://leafmap.org) if needed."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %pip install \"leafmap[maplibre]\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import numpy as np\n",
+    "import leafmap.maplibregl as leafmap"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To run this notebook, you will need an [API key](https://docs.maptiler.com/cloud/api/authentication-key/) from [MapTiler](https://www.maptiler.com/cloud/). Once you have the API key, you can set it as an environment variable in your notebook or script as follows:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# os.environ[\"MAPTILER_KEY\"] = \"YOUR_API_KEY\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "MAPTILER_KEY = os.environ.get(\"MAPTILER_KEY\")\n",
+    "style = f\"https://api.maptiler.com/maps/streets/style.json?key={MAPTILER_KEY}\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "# Generate the icon data\n",
+    "width = 64  # The image will be 64 pixels square\n",
+    "height = 64\n",
+    "bytes_per_pixel = 4  # Each pixel is represented by 4 bytes: red, green, blue, and alpha\n",
+    "data = np.zeros((width, width, bytes_per_pixel), dtype=np.uint8)\n",
+    "\n",
+    "for x in range(width):\n",
+    "    for y in range(width):\n",
+    "        data[y, x, 0] = int((y / width) * 255)  # red\n",
+    "        data[y, x, 1] = int((x / width) * 255)  # green\n",
+    "        data[y, x, 2] = 128  # blue\n",
+    "        data[y, x, 3] = 255  # alpha\n",
+    "\n",
+    "# Flatten the data array\n",
+    "flat_data = data.flatten()\n",
+    "\n",
+    "# Create the image dictionary\n",
+    "image_dict = {\n",
+    "    'width': width,\n",
+    "    'height': height,\n",
+    "    'data': flat_data.tolist(),\n",
+    "}\n",
+    "\n",
+    "m = leafmap.Map(center=[0, 0], zoom=1, style=style)\n",
+    "m.add_image(\"gradient\", image_dict)\n",
+    "source = {\n",
+    "    'type': 'geojson',\n",
+    "    'data': {\n",
+    "        'type': 'FeatureCollection',\n",
+    "        'features': [\n",
+    "            {'type': 'Feature', 'geometry': {'type': 'Point', 'coordinates': [0, 0]}}\n",
+    "        ],\n",
+    "    },\n",
+    "}\n",
+    "\n",
+    "layer = {\n",
+    "    'id': 'points',\n",
+    "    'type': 'symbol',\n",
+    "    'source': 'point',\n",
+    "    'layout': {'icon-image': 'gradient'},\n",
+    "}\n",
+    "\n",
+    "m.add_source('point', source)\n",
+    "m.add_layer(layer)\n",
+    "m"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![](https://i.imgur.com/qWWlnAm.png)"
+   ]
+  }
+ ],
+ "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": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

docs/maplibre/overview.md

@@ -38,6 +38,12 @@ Add an icon to the map from an external URL and use it in a symbol layer.
 
 [![](https://i.imgur.com/Nq1uV9d.png)](https://leafmap.org/maplibre/add_image)
 
+## Add a generated icon to the map
+
+Add an icon to the map that was generated at runtime.
+
+[![](https://i.imgur.com/qWWlnAm.png)](https://leafmap.org/maplibre/add_image_generated)
+
 ## Add a video
 
 Display a video on top of a satellite raster baselayer.

leafmap/maplibregl.py

@@ -1374,16 +1374,36 @@ def _read_image(self, image: str) -> Dict[str, Union[int, List[int]]]:
         else:
             raise ValueError("The image must be a URL or a local file path.")
 
-    def add_image(self, id: str, image: str) -> None:
+    def add_image(
+        self, id: str, image: Union[str, Dict], width: int = None, height: int = None
+    ) -> None:
         """Add an image to the map.
 
         Args:
             id (str): The layer ID of the image.
-            image (str): The URL or local file path to the image.
+            image (Union[str, Dict, np.ndarray]): The URL or local file path to
+                the image, or a dictionary containing image data, or a numpy
+                array representing the image.
+            width (int, optional): The width of the image. Defaults to None.
+            height (int, optional): The height of the image. Defaults to None.
 
         Returns:
             None
         """
+        import numpy as np
 
-        image_dict = self._read_image(image)
+        if isinstance(image, str):
+            image_dict = self._read_image(image)
+        elif isinstance(image, dict):
+            image_dict = image
+        elif isinstance(image, np.ndarray):
+            image_dict = {
+                "width": width,
+                "height": height,
+                "data": image.tolist(),
+            }
+        else:
+            raise ValueError(
+                "The image must be a URL, a local file path, or a numpy array."
+            )
         super().add_call("addImage", id, image_dict)

mkdocs.yml

@@ -142,8 +142,9 @@ nav:
           - maplibre/3d_indoor_mapping.ipynb
           - maplibre/3d_terrain.ipynb
           - maplibre/add_marker.ipynb
-          - maplibre/deckgl_layers.ipynb
+          - maplibre/deckgl_layer.ipynb
           - maplibre/add_image.ipynb
+          - maplibre/add_image_generated.ipynb
           - maplibre/fit_bounds.ipynb
           - maplibre/fly_to.ipynb
           - maplibre/fly_to_options.ipynb