interactive ml container

examples/interactive_ml/app/Dockerfile

@@ -0,0 +1,37 @@
+# Setup a Debian 12 based image with a Python virtualenv
+FROM debian:12-slim AS build
+RUN apt-get update && \
+    apt-get install --no-install-suggests --no-install-recommends --yes python3-venv gcc libpython3-dev && \
+    python3 -m venv /venv && \
+    /venv/bin/pip install --upgrade pip setuptools wheel
+
+# Install Geo Engine library and its dependencies
+FROM build AS build-venv
+COPY pyproject.toml setup.cfg setup.py /library/
+COPY geoengine /library/geoengine
+WORKDIR /library
+RUN /venv/bin/pip install --disable-pip-version-check .[dev,test,examples]
+
+# Copy the virtualenv into a distroless image
+# Hint: Use the `:debug` tag to get a shell in the image
+FROM gcr.io/distroless/python3-debian12
+COPY --from=build-venv /venv /venv
+
+# Copy the example notebook to run
+COPY examples/interactive_ml /app
+
+WORKDIR /app
+
+ENV GEOENGINE_INSTANCE_URL=https://zentrale.app.geoengine.io/api
+ENV GEOENGINE_SESSION_TOKEN=<SESSION_TOKEN>
+
+EXPOSE 8866
+
+ENTRYPOINT [ \
+    "/venv/bin/python3", \
+    "-m", \
+    "voila", \
+    "--no-browser", \
+    "--Voila.ip='0.0.0.0'", \
+    "app/Simple Random Forest Two-Class Classifier on Sentinel-2 Images.ipynb" \
+    ]

examples/interactive_ml/app/README.md

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+# Interactive ML App
+
+This app demonstrates a complete workflow for binary classification using Sentinel-2 satellite imagery and a Random Forest classifier. The workflow includes data acquisition, preprocessing, model training, and result visualization. Initially, the environment is set up and necessary libraries are imported. The spatial and temporal bounds for the data query are then defined through a query rectangle. A workflow is created to fetch and preprocess Sentinel-2 data, which is followed by the use of a labeling tool to create training data for water and non-water classes.
+
+## Local setup
+
+To run the app locally, you need to install the dependencies and start the app. You can install the dependencies with:
+
+```bash
+pip install --disable-pip-version-check -e .[dev,test,examples]
+
+GEOENGINE_INSTANCE_URL=https://zentrale.app.geoengine.io/api \
+GEOENGINE_SESSION_TOKEN=<SESSION_TOKEN> \
+./examples/interactive_ml/app/app.sh
+```
+
+The app will be available at [http://localhost:8866](http://localhost:8866).
+
+## Container setup
+
+To run the app in a container, you need to build the container image and start the container.
+You can build the container image with:
+
+```bash
+./examples/interactive_ml/app/build.sh
+
+podman run --rm \
+    -p 8866:8866 \
+    -e GEOENGINE_INSTANCE_URL=https://zentrale.app.geoengine.io/api \
+    -e GEOENGINE_SESSION_TOKEN=<SESSION_TOKEN> \
+    geoengine-interactive-ml:latest
+```
+
+### Upload to quay.io
+
+To upload the container image to quay.io, you need to log in and push the image.
+You can do this with:
+
+```bash
+podman login quay.io
+podman push geoengine-interactive-ml:latest quay.io/geoengine/geoengine-interactive-ml:latest
+```

examples/interactive_ml/app/Simple Random Forest Two-Class Classifier on Sentinel-2 Images.ipynb

@@ -18,6 +18,8 @@
    "outputs": [],
    "source": [
     "import ipyvuetify as vue\n",
+    "import IPython.display\n",
+    "import base64\n",
     "from dataclasses import dataclass\n",
     "from collections.abc import Callable, Coroutine\n",
     "from enum import Enum\n",
@@ -341,6 +343,22 @@
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open(\"assets/favicon.ico\", \"rb\") as image_file:\n",
+    "    favicon = base64.b64encode(image_file.read()).decode()\n",
+    "\n",
+    "favicon_changer = IPython.display.Javascript(f'''\n",
+    "    document.querySelector(\"link[rel='icon']\").href = \"data:image/x-icon;base64,{favicon}\";\n",
+    "''')\n",
+    "\n",
+    "IPython.display.display(favicon_changer)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -399,7 +417,7 @@
     "    padding: 0 !important;\n",
     "    margin: 0 !important;\n",
     "  }\n",
-    "</style>\n"
+    "</style>"
    ]
   },
   {
@@ -489,7 +507,7 @@
     "                self.error_bar,\n",
     "                vue.Html(tag='br'),\n",
     "            ]),\n",
-    "            vue.Footer(children=[vue.Col(children=['2024 – Geo Engine GmbH'], class_='text-center')], app=True),\n",
+    "            vue.Footer(children=[vue.Col(children=['2025 – Geo Engine GmbH'], class_='text-center')], app=True),\n",
     "        ]\n",
     "\n",
     "    def register_location_button(self, callback: Callable[[Location, str, str], None]) -> None:\n",
@@ -742,7 +760,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,

examples/interactive_ml/app/build.sh

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+#!/usr/bin/env bash
+
+SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
+
+podman build -f $SCRIPT_DIR/Dockerfile --tag geoengine-interactive-ml:latest .