Delete example_code

example_code/demo.py

@@ -1,34 +0,0 @@
-# Copyright (C) 2022 Intel Corporation
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing,
-# software distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions
-# and limitations under the License.
-
-import cv2
-from geti_sdk.deployment import Deployment
-from geti_sdk.utils import show_image_with_annotation_scene
-
-if __name__ == "__main__":
-    # Step 1: Load the deployment
-    deployment = Deployment.from_folder("../deployment")
-
-    # Step 2: Load the sample image
-    image = cv2.imread("../sample_image.jpg")
-    image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-
-    # Step 3: Send inference model(s) to CPU
-    deployment.load_inference_models(device="CPU")
-
-    # Step 4: Infer image
-    prediction = deployment.infer(image_rgb)
-
-    # Step 5: Visualization
-    show_image_with_annotation_scene(image_rgb, prediction)

example_code/demo_notebook.ipynb

@@ -1,156 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "86111f81-16f5-46e5-9010-1ef9e05a1571",
-   "metadata": {
-    "copyright": [
-     "INTEL CONFIDENTIAL",
-     "Copyright (C) 2022 Intel Corporation",
-     "This software and the related documents are Intel copyrighted materials, and your use of them is governed by",
-     "the express license under which they were provided to you (\"License\"). Unless the License provides otherwise,",
-     "you may not use, modify, copy, publish, distribute, disclose or transmit this software or the related documents",
-     "without Intel's prior written permission.",
-     "This software and the related documents are provided as is, with no express or implied warranties,",
-     "other than those that are expressly stated in the License."
-    ]
-   },
-   "source": [
-    "# Intel® Geti™ deployment demo notebook\n",
-    "This notebook demonstrates how to run inference for a deployed Intel® Geti™ project on your local machine. It contains the following steps:\n",
-    "1. Load the deployment for the project from the exported `deployment` folder\n",
-    "2. Load a sample image to run inference on\n",
-    "3. Prepare the deployment for inference by sending the model (or models) for the project to the CPU\n",
-    "4. Infer image\n",
-    "5. Visualize prediction"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a0ee561b-49fb-4f8b-9c7f-e4859e3fe99e",
-   "metadata": {},
-   "source": [
-    "### Step 1: Load the deployment"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d04d3e58-8cae-4491-86b6-fbc876fd5e4f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from geti_sdk.deployment import Deployment\n",
-    "\n",
-    "deployment = Deployment.from_folder(\"../deployment\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "713de7c8-0ac4-4865-b947-98ecbc4173fb",
-   "metadata": {},
-   "source": [
-    "### Step 2: Load the sample image"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5c61e01f-2c88-4f0d-ae18-88610cc13bf2",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import cv2\n",
-    "\n",
-    "image = cv2.imread(\"../sample_image.jpg\")\n",
-    "image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "40da9013-46f7-488d-972d-5ceddd54a60c",
-   "metadata": {},
-   "source": [
-    "### Step 3: Send inference model(s) to CPU"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f6b80e6f-57fa-421a-b71f-ffbd0847c0a9",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "deployment.load_inference_models(device='CPU')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "6f539adc-04e7-43b4-b113-99e7ff7f6482",
-   "metadata": {},
-   "source": [
-    "### Step 4: Infer image"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a0e72d41-ec75-4bfe-859b-7302463b9fb6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "prediction = deployment.infer(image_rgb)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "5f450bb5-29dc-4ac4-b5bb-4b02f350aacc",
-   "metadata": {},
-   "source": [
-    "### Step 5: Visualization"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "db0dd922-36aa-4203-bc02-76c17d12d8be",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from geti_sdk.utils import show_image_with_annotation_scene\n",
-    "\n",
-    "show_image_with_annotation_scene(image_rgb, prediction, show_in_notebook=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a342324f-3177-4d61-bee4-40b47d0f78f8",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "celltoolbar": "Edit 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": "3.8.10"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}

example_code/demo_ovms.ipynb

@@ -1,421 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "copyright": [
-     "INTEL CONFIDENTIAL",
-     "Copyright (C) 2023 Intel Corporation",
-     "This software and the related documents are Intel copyrighted materials, and your use of them is governed by",
-     "the express license under which they were provided to you (\"License\"). Unless the License provides otherwise,",
-     "you may not use, modify, copy, publish, distribute, disclose or transmit this software or the related documents",
-     "without Intel's prior written permission.",
-     "This software and the related documents are provided as is, with no express or implied warranties,",
-     "other than those that are expressly stated in the License."
-    ]
-   },
-   "source": [
-    "# Serving Intel® Geti™ models with OpenVINO Model Server\n",
-    "This notebook shows how to set up an OpenVINO model server to serve the models trained\n",
-    "in your Intel® Geti™ project. It also shows how to use the Geti SDK as a client to\n",
-    "make inference requests to the model server.\n",
-    "\n",
-    "# Contents\n",
-    "\n",
-    "1. **OpenVINO Model Server**\n",
-    "    1. Requirements\n",
-    "    2. Generating the model server configuration\n",
-    "    3. Launching the model server\n",
-    "\n",
-    "2. **OVMS inference with Geti SDK**\n",
-    "    1. Loading inference model and sample image\n",
-    "    2. Requesting inference\n",
-    "    3. Inspecting the results\n",
-    "\n",
-    "3. **Conclusion**\n",
-    "    1. Cleaning up\n",
-    "\n",
-    "> **NOTE**: This notebook will set up a model server on the same machine that will be\n",
-    "> used as a client to request inference. In a real scenario you'd most likely\n",
-    "> want the server and the client to be different physical machines. The steps to set up\n",
-    "> OVMS on a remote server are the same as for the local server outlined in this\n",
-    "> notebook, but additional network configuration and security measures are most likely\n",
-    "> required.\n",
-    "\n",
-    "# OpenVINO Model Server\n",
-    "## Requirements\n",
-    "We will be running the OpenVINO Model Server (OVMS) with Docker. Please make sure you\n",
-    "have docker available on your system. You can install it by following the instructions\n",
-    "[here](https://docs.docker.com/get-docker/).\n",
-    "\n",
-    "## Generating the model server configuration\n",
-    "The `deployment` that was downloaded from the Intel® Geti™ platform can be used to create\n",
-    "the configuration files that are needed to set up an OpenVINO model server for your project.\n",
-    "\n",
-    "The cell below shows how to create the configuration. Running this cell should create\n",
-    "a folder called `ovms_models` in a temporary directory. The `ovms_models` folder\n",
-    "contains the models and the configuration files required to run OVMS for the Intel®\n",
-    "Geti™ project."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
-    },
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "import tempfile\n",
-    "\n",
-    "from geti_sdk.deployment import Deployment\n",
-    "\n",
-    "deployment_path = os.path.join(\"..\", \"deployment\")\n",
-    "\n",
-    "# Load the Geti deployment\n",
-    "deployment = Deployment.from_folder(deployment_path)\n",
-    "\n",
-    "# Creating the OVMS configuration for the deployment\n",
-    "# First, we'll create a temporary directory to store the config files\n",
-    "ovms_config_path = os.path.join(tempfile.mkdtemp(), \"ovms_models\")\n",
-    "\n",
-    "# Next, we generate the OVMS configuration and save it\n",
-    "deployment.generate_ovms_config(output_folder=ovms_config_path)\n",
-    "\n",
-    "print(f\"Configuration for OpenVINO Model Server was created at '{ovms_config_path}'\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "pycharm": {
-     "name": "#%% md\n"
-    }
-   },
-   "source": [
-    "## Launching the model server\n",
-    "As mentioned before, we will run OVMS in a Docker container. First, we need to make sure\n",
-    "that we have the latest OVMS image on our system. Run the cell below to pull the image."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
-    },
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "! docker pull openvino/model_server:latest"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "pycharm": {
-     "name": "#%% md\n"
-    }
-   },
-   "source": [
-    "Next, we have to start the container with the configuration that we just generated. This\n",
-    "is done in the cell below.\n",
-    "\n",
-    "> NOTE: The cell below starts the OVMS container and sets it up to listen for inference\n",
-    "> requests on port 9000 on your system. If this port is already occupied the `docker run`\n",
-    "> command will fail and you may need to try a different port number."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
-    },
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "# Launch the OVMS container\n",
-    "result = ! docker run -d --rm -v {ovms_config_path}:/models -p 9000:9000 --name ovms_demo openvino/model_server:latest --port 9000 --config_path /models/ovms_model_config.json\n",
-    "\n",
-    "# Check that the container was created successfully\n",
-    "if len(result) == 1:\n",
-    "    container_id = result[0]\n",
-    "    print(f\"OVMS container with ID '{container_id}' created.\")\n",
-    "else:\n",
-    "    # Anything other than 1 result indicates that something went wrong\n",
-    "    raise RuntimeError(result)\n",
-    "\n",
-    "# Check that the container is running properly\n",
-    "container_info = ! docker container inspect {container_id}\n",
-    "container_status = str(container_info.grep(\"Status\"))\n",
-    "\n",
-    "if not container_status or not \"running\" in container_status:\n",
-    "    raise RuntimeError(\n",
-    "        f\"Invalid ovms docker container status found: {container_status}. Most \"\n",
-    "        f\"likely the container has not started properly.\"\n",
-    "    )\n",
-    "print(\"OVMS container is up and running.\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "pycharm": {
-     "name": "#%% md\n"
-    }
-   },
-   "source": [
-    "That's it! If all went well the cell above should print the ID of the container that\n",
-    "was created. This can be used to identify your container if you have a lot of docker\n",
-    "containers running on your system.\n",
-    "\n",
-    "# OVMS inference with Geti SDK\n",
-    "Now that the OVMS container is running, we can use the Geti SDK to talk to it and make an\n",
-    "inference request. The remaining part of this notebook shows how to do so.\n",
-    "\n",
-    "## Loading inference model and sample image\n",
-    "In the first part of this notebook we created configuration files for OVMS, using the\n",
-    "`deployment` that was generated for your Intel® Geti™ project. To do inference, we need\n",
-    "to connect the deployment to the OVMS container that is now running. This is done in the\n",
-    "cell below."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
-    },
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "# Load the inference models by connecting to OVMS on port 9000\n",
-    "deployment.load_inference_models(device=\"http://localhost:9000\")\n",
-    "\n",
-    "print(\"Connected to OpenVINO Model Server.\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "pycharm": {
-     "name": "#%% md\n"
-    }
-   },
-   "source": [
-    "You should see some output indicating that the connection to OVMS was made successfully.\n",
-    "If you see any errors at this stage, make sure your OVMS container is running and that the\n",
-    "port number is correct.\n",
-    "\n",
-    "Next up, we'll load a sample image from the project to run inference on"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
-    },
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "import cv2\n",
-    "\n",
-    "# Load the sample image\n",
-    "image = cv2.imread(\"../sample_image.jpg\")\n",
-    "image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n",
-    "\n",
-    "# Show the image in the notebook\n",
-    "from IPython.display import display\n",
-    "from PIL import Image\n",
-    "\n",
-    "display(Image.fromarray(image_rgb))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "pycharm": {
-     "name": "#%% md\n"
-    }
-   },
-   "source": [
-    "## Requesting inference\n",
-    "Now that everything is set up, making an inference request is very simple:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
-    },
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "import time\n",
-    "\n",
-    "t_start = time.time()\n",
-    "prediction = deployment.infer(image_rgb)\n",
-    "t_end = time.time()\n",
-    "\n",
-    "print(\n",
-    "    f\"OVMS inference on sample image completed in {(t_end - t_start) * 1000:.1f} milliseconds.\"\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "pycharm": {
-     "name": "#%% md\n"
-    }
-   },
-   "source": [
-    "## Inspecting the results\n",
-    "Note that the code to request inference is exactly the same as for the case when the model\n",
-    "is loaded on the CPU (see `demo_notebook.ipynb`). Like The `prediction` can be shown using\n",
-    "the Geti SDK visualization utility function."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
-    },
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "from geti_sdk.utils import show_image_with_annotation_scene\n",
-    "\n",
-    "show_image_with_annotation_scene(image_rgb, prediction, show_in_notebook=True);"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "jupyter": {
-     "outputs_hidden": false
-    },
-    "pycharm": {
-     "name": "#%% md\n"
-    }
-   },
-   "source": [
-    "# Conclusion\n",
-    "That's all there is to it! Of course in practice the client would request inference\n",
-    "from an OpenVINO model server on a different physical machine, in contrast to the\n",
-    "example here where client and server are running on the same machine.\n",
-    "\n",
-    "The steps outlined in this notebook can be used as a basis to set up a remote\n",
-    "client/server combination, but please note that additional network configuration will\n",
-    "be required (along with necessary security measures).\n",
-    "\n",
-    "## Cleaning up\n",
-    "To clean up, we'll stop the OVMS docker container that we started. This will\n",
-    "automatically remove the container. After that, we'll delete the temporary directory\n",
-    "we created to store the config files."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Stop the container\n",
-    "result = ! docker stop {container_id}\n",
-    "\n",
-    "# Check if removing the container worked correctly\n",
-    "if result[0] == container_id:\n",
-    "    print(f\"OVMS container '{container_id}' stopped and removed successfully.\")\n",
-    "else:\n",
-    "    print(\n",
-    "       \"An error occurred while removing OVMS docker container. Most likely the container \"\n",
-    "       \"was already removed. \"\n",
-    "    )\n",
-    "    print(f\"The docker daemon responded with the following error: \\n{result}\")\n",
-    "    \n",
-    "# Remove the temporary directory with the OVMS configuration\n",
-    "import shutil\n",
-    "\n",
-    "temp_dir = os.path.dirname(ovms_config_path)\n",
-    "try:\n",
-    "    shutil.rmtree(temp_dir)\n",
-    "    print(\"Temporary configuration directory removed successfully.\")\n",
-    "except FileNotFoundError:\n",
-    "    print(\n",
-    "        f\"Temporary directory with OVMS configuration '{temp_dir}' was \"\n",
-    "        f\"not found on the system. Most likely it is already removed.\"\n",
-    "    )"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "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": "3.8.16"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}

example_code/requirements-notebook.txt

@@ -1,6 +0,0 @@
-# Requirements for running the `demo_notebook.ipynb` and `demo_ovms.ipynb` Jupyter notebooks
-geti-sdk==1.5.*
-jupyterlab==3.6.*
-opencv-python>=4.5.0
-Pillow>=9.4.0
-ipython>=8.10.0

example_code/requirements.txt

@@ -1,3 +0,0 @@
-# Base requirements for the deployment
-geti-sdk==1.5.*
-opencv-python>=4.5.0